Advanced Topics in HR Employee Selection and Staffing MGT 467/667 Dr. Yvonne Stedham MGT 467/667 Dr. Yvonne Stedham.

Advanced Topics in HR

Employee Selection and Staffing

MGT 467/667

Dr. Yvonne Stedham

MGT 467/667

Dr. Yvonne Stedham

Pre-requisites

MGT 323

Organizational Behavior

MGT 367

Human Resource Management

MGT 323

Organizational Behavior

MGT 367

Human Resource Management

Course Content and Purpose

• Major? Management, IB, Other

• Focus on HR?Management degree with concentration in

HRPractical background in HRLimited interest in HR

• Major? Management, IB, Other

• Focus on HR?Management degree with concentration in

HRPractical background in HRLimited interest in HR

4

Managerial Skills

Technical, Conceptual, Human Relations Skills

– Human Relations Skills (Examples)

• Listening• Persuading• Goal setting • Providing Feedback • Running meetings• Empowering people

Technical, Conceptual, Human Relations Skills

– Human Relations Skills (Examples)

• Listening• Persuading• Goal setting • Providing Feedback • Running meetings• Empowering people

• Resolving conflicts

• Coaching• Interviewing

• Building Teams

Course Materials available on

http://www.business.unr.edu/faculty/stedham/ http://www.business.unr.edu/faculty/stedham/

http://www.business.unr.edu/faculty/stedham/

http://www.business.unr.edu/faculty/stedham/

Readings

• Several Readings In-class handout, website, or find online

• Five with assignments or quizzes

• Sign-up for presentations

• Several Readings In-class handout, website, or find online

• Five with assignments or quizzes

• Sign-up for presentations

Employee Selection

Course Introduction 1. Content Overview2. Format Overview

(Syllabus) – Readings/ HRMagazine/WSJ/Fortune

SHRM – Society for Human Resource Management (www.shrm.org)

Personal Introductions• Instructor• Students – Background Sheet

Course Introduction 1. Content Overview2. Format Overview

(Syllabus) – Readings/ HRMagazine/WSJ/Fortune

SHRM – Society for Human Resource Management (www.shrm.org)

Personal Introductions• Instructor• Students – Background Sheet

http://www.shrm.org/

http://www.shrm.org/

Employee Selection

Course Introduction

What do you know about HR?

Organizational Performance and HR

External Environment

Course Introduction


Organizational Performance and HR


What do you know about HR?Table Tents

1. What is Human Resource Management? How does it contribute to the success of an organization?

2. List the specific functions entailed in HRM.

3. What does KSAs stand for? What is a JE and a JA? What is the FMLA?

4. List the most important federal anti-discrimination laws.

5. What are the primary provisions of Title VII? What is a BFOQ?

1. What is Human Resource Management? How does it contribute to the success of an organization?

2. List the specific functions entailed in HRM.

3. What does KSAs stand for? What is a JE and a JA? What is the FMLA?

4. List the most important federal anti-discrimination laws.

5. What are the primary provisions of Title VII? What is a BFOQ?


6. Distinguish two types of Sexual Harassment.

7. Does money motivate employees? Explain.

8. How do you determine whether an individual has the skills and knowledge required for job?

9. What is the primary purpose of an employee interview?

10. To what extent is employee turnover desirable?

6. Distinguish two types of Sexual Harassment.

7. Does money motivate employees? Explain.

8. How do you determine whether an individual has the skills and knowledge required for job?

9. What is the primary purpose of an employee interview?

10. To what extent is employee turnover desirable?

This Course The Staffing/Employment Function

• The most important HR function

• Budget and time spent

• Staffing• Mutual process by which • the individual and the organization become

matched to • form the employment relationship.

• Mutual Process: Series of interrelated activities - Recruitment, Selection, Decision Making, job offers, hiring.

• The most important HR function

• Budget and time spent

• Staffing• Mutual process by which • the individual and the organization become

matched to • form the employment relationship.

• Mutual Process: Series of interrelated activities - Recruitment, Selection, Decision Making, job offers, hiring.

Definitions

Recruitment Generating a pool of qualified applicants

Selection Assessing/Measuring Applicant KSAs –

Development of KSA Measures

Recruitment Generating a pool of qualified applicants

Selection Assessing/Measuring Applicant KSAs –

Development of KSA Measures

Definitions

• Selection • The process of obtaining • and using information • about job applicants • to determine who should be hired.

• Focus here is on how to collect relevant info on applicants’ KSA’s.

• Selection • The process of obtaining • and using information • about job applicants • to determine who should be hired.

• Focus here is on how to collect relevant info on applicants’ KSA’s.

Course Format

• Syllabus• Syllabus

Selection and the Bottom Line - A Framework

• Why a course in employee selection?

• What is the relationship between organizational effectiveness and HRM?

• Why a course in employee selection?

• What is the relationship between organizational effectiveness and HRM?

HR and Organizational Performance

• What is an organization?

• What is organizational effectiveness?

• How does HR contribute?

• What is an organization?

• What is organizational effectiveness?

• How does HR contribute?

HR and Org effectiveness

• Individual effectiveness is the foundation for organizational effectiveness.

• Individual effectiveness depends on ….

• Individual effectiveness is the foundation for organizational effectiveness.

• Individual effectiveness depends on ….


Individual effectiveness = Performance

Individual effectiveness = f(Ability,Motivation)

Performance = Ability * Motivation

Individual effectiveness = Performance

Individual effectiveness = f(Ability,Motivation)


Individual Performance

19

Match

20

21

The HRM Framework

External EnvironmentExternal EnvironmentLegal Environment

Economy Labor Market Social Environment

MATCHMATCH

HR Outcomes

Job SatisfactionOrg. CommitmentAttractionAttendanceTurnover

HR ActivitiesRecruitment

SelectionCompensation

BenefitsTraining

Labor RelationsEmployee Relations

PERSON•KSAs•Needs

JOB•KSAs

•Rewards

Personal Introductions

• Students – Table Tents and Background Sheets?

Name and MajorHR Games?Share a “hiring” experience

• Students – Table Tents and Background Sheets?

Name and MajorHR Games?Share a “hiring” experience

Introductory Exercise

1. Have you ever been involved in hiring an employee? Describe.

2. Did you like being involved in the hiring process? Why/why not?

3. When selecting an employee, what do you think is the most important criterion to consider? Why?

4. How do you know whether you have an effective hiring/selection process in place?

1. Have you ever been involved in hiring an employee? Describe.

2. Did you like being involved in the hiring process? Why/why not?

3. When selecting an employee, what do you think is the most important criterion to consider? Why?

4. How do you know whether you have an effective hiring/selection process in place?

A Word about Recruitment

• Quantity?

• Type – what KSAs?

• Size of applicant pool to fill how many positions?– Yield Ratios

• Sources?– Formal/Informal– Relevant Labor Market

• Timing

• Quantity?

• Type – what KSAs?

• Size of applicant pool to fill how many positions?– Yield Ratios

• Sources?– Formal/Informal– Relevant Labor Market

• Timing

SNC – HR Internship

• I wanted to inform you of a new internship position that just opened up at SNC -

Training and Development Intern. We are looking for an energetic individual, preferably Junior or Senior, with strong technical/PC skills, excellent verbal and written communication, and strong interest in Org Development/Training to join our team. Work hours range between 7:30-5:30, working with the individual's school schedule, preferably committing 20-32 hours a week. This is a great opportunity to gain first-hand corporate experience in the training and development field. As you may know, we've had two recent successful HR interns from UNR: - Amy Mendel, training intern, joined us in February, graduated in May, and recently landed a position outside of SNC as a Training and Development Manager - Adrian Nunez, HR Intern, joined us after graduation in May and has received a permanent offer to stay on our HR Team supporting our Corporate Org Development Manager If you know of students that you recommend for this position, please have them contact me via email with their resume. We are looking to fill this position as soon as possible, and will extend an offer as soon as the right candidate comes our way! Feel free to contact me if you have any questions- Kind Regards, Pam Durfee, PHRHuman Resources444 Salomon Circle Sparks, NV 89434Ph: 775.849.6172 Faax: 775.201.0672

• I wanted to inform you of a new internship position that just opened up at SNC -

Training and Development Intern. We are looking for an energetic individual, preferably Junior or Senior, with strong technical/PC skills, excellent verbal and written communication, and strong interest in Org Development/Training to join our team. Work hours range between 7:30-5:30, working with the individual's school schedule, preferably committing 20-32 hours a week. This is a great opportunity to gain first-hand corporate experience in the training and development field. As you may know, we've had two recent successful HR interns from UNR: - Amy Mendel, training intern, joined us in February, graduated in May, and recently landed a position outside of SNC as a Training and Development Manager - Adrian Nunez, HR Intern, joined us after graduation in May and has received a permanent offer to stay on our HR Team supporting our Corporate Org Development Manager If you know of students that you recommend for this position, please have them contact me via email with their resume. We are looking to fill this position as soon as possible, and will extend an offer as soon as the right candidate comes our way! Feel free to contact me if you have any questions- Kind Regards, Pam Durfee, PHRHuman Resources444 Salomon Circle Sparks, NV 89434Ph: 775.849.6172 Faax: 775.201.0672


1. Labor Markets, Global Economic Crisis, and HRM

2. Legal Environment

1. Labor Markets, Global Economic Crisis, and HRM

2. Legal Environment

Economic conditions

• Current conditions

• What?

• Why?

• Predictions?

• Effect on HRM?

• Current conditions

• What?

• Why?

• Predictions?

• Effect on HRM?

Labor Market

Demand – Derived Demand • Quantity - Job growth • Quality - Types of jobs and KSA’s

Supply – Workforce Quantity and Quality • Number• Composition – Diversity, Generations, Values• KSA’s

Demand – Derived Demand • Quantity - Job growth • Quality - Types of jobs and KSA’s

Supply – Workforce Quantity and Quality • Number• Composition – Diversity, Generations, Values• KSA’s

Labor Market

Psychological ContractPsychological Contract

What is the number one reason for employees to

quit their job?

What is the number one reason for employees to

quit their job?

Study on Turnover in Gaming

• Importance of perceptions of “fairness”

• Following rules and procedures

• Making arbitrary decisions

• Consistency

• Importance of perceptions of “fairness”

• Following rules and procedures

• Making arbitrary decisions

• Consistency

What is important to employees?

Job attributes and rewardsJob attributes and rewards

How do you believe a typical non-supervisory employee would rank the following 10 job attributes?

___ Job security

____Good wages

____Promotion and growth in the organization

____Good working conditions

____Personal loyalty to employees

____Tactful discipline

____Sympathetic help with personal problems

____Interesting Work

____Full appreciation of work done

____Feeling of being in on things

___ Job security

____Good wages

____Promotion and growth in the organization

____Good working conditions

____Personal loyalty to employees

____Tactful discipline

____Sympathetic help with personal problems

____Interesting Work

____Full appreciation of work done

____Feeling of being in on things

Survey Results

1. Interesting Work2. Full appreciation of work done3. Feeling of being in on things4. Job security5. Good wages6. Promotion and growth in the organization7. Good working conditions8. Personal loyalty to employees9. Tactful discipline10. Sympathetic help with personal problems

1. Interesting Work2. Full appreciation of work done3. Feeling of being in on things4. Job security5. Good wages6. Promotion and growth in the organization7. Good working conditions8. Personal loyalty to employees9. Tactful discipline10. Sympathetic help with personal problems

Role of HR

The Human Equation Jeffrey Pfeffer

Seven common practices:

1. Employment security.

2. Selective hiring,

3. Self-managed teams and decentralization,

4. High compensation,

5. Extensive training,

6. Reduction of status differences,

7. Sharing information

The Human Equation Jeffrey Pfeffer

Seven common practices:

1. Employment security.

2. Selective hiring,

3. Self-managed teams and decentralization,

4. High compensation,

5. Extensive training,

6. Reduction of status differences,

7. Sharing information

Role of HR

The Human Equation

• Theoretical foundation – how/why do these practices work?

• Increased involvement and commitment, more control and say in their work, work smarter because they are encouraged to build skills and competence.

The Human Equation

• Theoretical foundation – how/why do these practices work?

• Increased involvement and commitment, more control and say in their work, work smarter because they are encouraged to build skills and competence.

HRM – Four Pillars

• Involvement

• Communication

• Commitment

• Community

• Involvement

• Communication

• Commitment

• Community

Labor Market

Generations at work

1. WWII Generation 60+

2. Baby Boom 40-60

3. Generation X 20-40

4. Millennial Generation birth-20 (Gen Y)

Generations at work

1. WWII Generation 60+

2. Baby Boom 40-60

3. Generation X 20-40

4. Millennial Generation birth-20 (Gen Y)

Generations

WWII 60+

Outlook: practical

Work Ethic: dedicated

View of Authority: respectful

Leadership by: hierarchy

Relationship: personal sacrifice

Perspective: Civic

WWII 60+

Outlook: practical

Work Ethic: dedicated

View of Authority: respectful

Leadership by: hierarchy

Relationship: personal sacrifice

Perspective: Civic

Generations

Baby Boom 40-60

Outlook: optimistic

Work Ethic: driven

View of Authority: love/hate

Leadership by: consensus

Relationship: personal gratification

Perspective: team

Also: workholic – defined by work, competitve, trophies, rebellion

Baby Boom 40-60

Outlook: optimistic

Work Ethic: driven

View of Authority: love/hate

Leadership by: consensus

Relationship: personal gratification

Perspective: team

Also: workholic – defined by work, competitve, trophies, rebellion

Generations

Generation X 20-40

Outlook: skeptical

Work Ethic: balanced

View of Authority: unimpressed

Leadership by: competence

Relationship: reluctant to commit

Perspective: self

Generation X 20-40

Outlook: skeptical

Work Ethic: balanced

View of Authority: unimpressed

Leadership by: competence

Relationship: reluctant to commit

Perspective: self

Generations

Millennials (Y) 20 and younger

environmentally conscious

connected

more tolerant of differences

generally optimistic

achievement oriented

team players

sociable

want to fit in not revolutionize

Millennials (Y) 20 and younger

environmentally conscious

connected

more tolerant of differences

generally optimistic

achievement oriented

team players

sociable

want to fit in not revolutionize

Generations in the Workplace

WWII BB X Y

Outlook practical optimistic skeptical connected

Work Ethic

dedicated driven balance balance

Leader

ship

hierarchy consensus competence competence

Relation

ship

personal sacrifice

personal gratification

reluctant to commit

?

Generations in the Workplace

• Implications for Management, HR, and Selection????

• Implications for Management, HR, and Selection????

Summary

Labor MarketDemand

- QUN and - QUL - Labor Shortage

Supply - QUN and - QUL - Composition and KSA type and level;

and, needs and values of employees

Labor MarketDemand

- QUN and - QUL - Labor Shortage

Supply - QUN and - QUL - Composition and KSA type and level;

and, needs and values of employees

Summary

• Labor MarketDiversity of valuesGenerational Differences

• WWII• Baby Boomers• Generation X• Generation Y

• Labor MarketDiversity of valuesGenerational Differences

• WWII• Baby Boomers• Generation X• Generation Y

Legal Environment

The Employment Relationship

• Exchange relationship

• Psychological Contract

• Employment Contract Formal agreement, voluntary: Defines and

governs the terms and conditions of the employment relationship; promises and expectations … change with time

Written or oral --- both are legally enforceable

The Employment Relationship

• Exchange relationship

• Psychological Contract

• Employment Contract Formal agreement, voluntary: Defines and

governs the terms and conditions of the employment relationship; promises and expectations … change with time

Written or oral --- both are legally enforceable

Common Law

• Refers to laws applied in the English-speaking world when there were few statutes.

• Courts wrote opinions explaining the bases for their decisions

• These opinions became precedents for later decisions in similar cases

• Refers to laws applied in the English-speaking world when there were few statutes.

• Courts wrote opinions explaining the bases for their decisions

• These opinions became precedents for later decisions in similar cases

Workplace Torts

A Tort is a “civil wrong”

a violation of a duty by the ER that leads to harm or damages suffered by others

A Tort is a “civil wrong”

a violation of a duty by the ER that leads to harm or damages suffered by others

Workplace Torts

Are

breaches of legal duty by ER when establishing or modifying the initial relationship (common

law)

Are

breaches of legal duty by ER when establishing or modifying the initial relationship (common

law)

Workplace Torts

1. Fraud or misrepresentation: lie/mislead applicant when communicating conditions and terms -> ER violates a duty to be truthful in the presentation of information

2. Negligent hiring: ER violates duty to protect Ees and customers against unreasonable and foreseeable risk of harm

3. Wrongful Discharge

1. Fraud or misrepresentation: lie/mislead applicant when communicating conditions and terms -> ER violates a duty to be truthful in the presentation of information

2. Negligent hiring: ER violates duty to protect Ees and customers against unreasonable and foreseeable risk of harm

3. Wrongful Discharge

Wrongful Discharge

• Tort – civil wrong – due process – just cause

• Good faith – fair dealing• Implied contract

– Contract renewal– Performance evals

• Fire for cause (Employment at Will)1. Violation of company policy2. Poor performance

• Tort – civil wrong – due process – just cause

• Good faith – fair dealing• Implied contract

– Contract renewal– Performance evals

• Fire for cause (Employment at Will)1. Violation of company policy2. Poor performance

Need for Laws and Regulations

Balance of Power Laws limit discretion of ER in establishment of terms and conditions

Protection of EEsEmployment Standards - Minimum

acceptable terms and conditions of employment … min. wage, overtime, safety and health (FLSA 1938, OSHA)

Balance of Power Laws limit discretion of ER in establishment of terms and conditions

Protection of EEsEmployment Standards - Minimum

acceptable terms and conditions of employment … min. wage, overtime, safety and health (FLSA 1938, OSHA)

Need for laws

Individual RightsLabor Relations,

Civil Rights Protection,

Restrictions on employment-at-will

Consistency of Treatment: Procedural justice Standardized Systems

Individual RightsLabor Relations,

Civil Rights Protection,

Restrictions on employment-at-will

Consistency of Treatment: Procedural justice Standardized Systems

Legal Environment

Protection of ERs

Permissble and impermissible practices: what is OK … e.g., to use ability tests

• Administrative predictability and stability

Protection of ERs

Permissble and impermissible practices: what is OK … e.g., to use ability tests

• Administrative predictability and stability

Sources of Laws and Regulations

Common LawEngland; Court-made Law; Case-by-

case decisions Precedence (Germany and other country code-based law); States – develop and administer own common law.

Constitutional LawSupersedes; Prohibits deprivation of

employment right without due process.

Common LawEngland; Court-made Law; Case-by-

case decisions Precedence (Germany and other country code-based law); States – develop and administer own common law.

Constitutional LawSupersedes; Prohibits deprivation of

employment right without due process.

Legal Environment

Statutory Law Derived from written statutes that are passed

by legislative bodies (Federal – Congress; State – Legislature/Assemblies; Local – Municipal/Councils)

AgenciesInterpret, administer, enforce law. DOL

(OFCCP); EEOC - publish rules and regulatory guidelines that are given “great deference” by courts.

Statutory Law Derived from written statutes that are passed

by legislative bodies (Federal – Congress; State – Legislature/Assemblies; Local – Municipal/Councils)

AgenciesInterpret, administer, enforce law. DOL

(OFCCP); EEOC - publish rules and regulatory guidelines that are given “great deference” by courts.

EEO Framework

U.S. Constitution• 5th Amendment

– Due Process of law --- Prohibition upon federal government;

– no person shall be deprived of life, liberty, or property; does not speak directly to specific subjects such as employment

Courts prefer to defer to existing statutory laws because it is more specific!!

• 14th Amendment– Prohibition for States to enacts any law that does not

“guarantee” equal protection for all.

U.S. Constitution• 5th Amendment

– Due Process of law --- Prohibition upon federal government;

– no person shall be deprived of life, liberty, or property; does not speak directly to specific subjects such as employment

Courts prefer to defer to existing statutory laws because it is more specific!!

• 14th Amendment– Prohibition for States to enacts any law that does not

“guarantee” equal protection for all.

EEO Framework

Statutory Laws• Civil Rights Act 1866:

• Right to make and enforce contracts for employment … for all citizens as enjoyed by white citizens.

Civil Rights Act of 1871:• Right to sue if deprived of any rights or privileges guaranteed

by the Constitution and laws for ALL citizens. Must show intention.

• Equal Pay Act 1963:• Equal pay for equal work regardless of SEX (female

employees only); amendment to FLSA .

Statutory Laws• Civil Rights Act 1866:

• Right to make and enforce contracts for employment … for all citizens as enjoyed by white citizens.

Civil Rights Act of 1871:• Right to sue if deprived of any rights or privileges guaranteed

by the Constitution and laws for ALL citizens. Must show intention.

• Equal Pay Act 1963:• Equal pay for equal work regardless of SEX (female

employees only); amendment to FLSA .

EPA

• Equal pay for equal work regardless of SEX (female employees only); amendment to FLSA .

“Equal” Work: Substantially similar – Requirements concerning skill, effort, responsibilities, working conditions.

Exceptions: Seniority; Merit; Quantity of production

Note: If in violation of EPA, ER may not LOWER wages.

• Consider --- Internal equity and job evaluation; • Comparable worth.

• Equal pay for equal work regardless of SEX (female employees only); amendment to FLSA .

“Equal” Work: Substantially similar – Requirements concerning skill, effort, responsibilities, working conditions.

Exceptions: Seniority; Merit; Quantity of production

Note: If in violation of EPA, ER may not LOWER wages.

• Consider --- Internal equity and job evaluation; • Comparable worth.

Title VII of CRA 1964:

Coverage: ERs with 15 or more employees; Federal, State, Local governments; Educational Institutions; Employment Agencies; Labor Unions; Congress

Not covered: Private Clubs; Religious Organizations.

CRA 1964: Several Titles each focusing on discrimination in a different “sector” of society (education, right to vote,… ) Title VII focuses on discrimination in employment.

Coverage: ERs with 15 or more employees; Federal, State, Local governments; Educational Institutions; Employment Agencies; Labor Unions; Congress

Not covered: Private Clubs; Religious Organizations.

CRA 1964: Several Titles each focusing on discrimination in a different “sector” of society (education, right to vote,… ) Title VII focuses on discrimination in employment.

Title VII

Enforcement: EEOC

Language of TVII:

703 (a)

Employer may not discriminate on the basis of race, color, national origin, sex, and religion in any employment decision.

Enforcement: EEOC

Language of TVII:

703 (a)

Employer may not discriminate on the basis of race, color, national origin, sex, and religion in any employment decision.

Title VII

Color: White, black, yellow, brown, red. Race: Local geographic or global human

population distinguished by genetically transmitted physical characteristics … Caucasian; Negro; Hispanic; Oriental; Indian.

National Origin: Citizenship; Heritage; Any country, nation.

Religion: All kinds; not associated with any of the other characteristics; Christian, Hindu, Muslim, Buddhist.

Color: White, black, yellow, brown, red. Race: Local geographic or global human

population distinguished by genetically transmitted physical characteristics … Caucasian; Negro; Hispanic; Oriental; Indian.

National Origin: Citizenship; Heritage; Any country, nation.

Religion: All kinds; not associated with any of the other characteristics; Christian, Hindu, Muslim, Buddhist.

Title VII

• 703 (b) …. Nondiscriminatory apprenticeship program

• 704 (a) …. Unlawful to discriminate … if opposed unlawful employment practice … assisted in TVII investigation.

• 704 (b) …. Prohibits ads concerning employment indicating preference for any of the prohibited factors.

• 1978 Amendment: – Pregnancy Discrimination Act --- – prohibits discrimination on the basis of pregnancy,

childbirth, or related condition. – Reinstatement right for similar position; no loss of

seniority; – coverage of disability insurance.

• 703 (b) …. Nondiscriminatory apprenticeship program

• 704 (a) …. Unlawful to discriminate … if opposed unlawful employment practice … assisted in TVII investigation.

• 704 (b) …. Prohibits ads concerning employment indicating preference for any of the prohibited factors.

• 1978 Amendment: – Pregnancy Discrimination Act --- – prohibits discrimination on the basis of pregnancy,

childbirth, or related condition. – Reinstatement right for similar position; no loss of

seniority; – coverage of disability insurance.

Title VII - Exemptions

• that are written into the law

• Discrimination on the basis of the “protected factors” is permissible when such qualification is a bona-fide occupationl qualification (BFOQ)

• = reasonably necessary to the operation of that particular business or enterprise;

• burden of proof is with ER; • very narrowly interpreted --- preferences of ER, coworkers,

clients are irrelevant.

• Seniority Systems: Bona fide seniority or merit systems are lawful if no intention to discriminate; job or departmental systems are not seen as “bona fide”, plant or company-wide systems are seen as “bona fide”.

• that are written into the law

• Discrimination on the basis of the “protected factors” is permissible when such qualification is a bona-fide occupationl qualification (BFOQ)

• = reasonably necessary to the operation of that particular business or enterprise;

• burden of proof is with ER; • very narrowly interpreted --- preferences of ER, coworkers,

clients are irrelevant.

• Seniority Systems: Bona fide seniority or merit systems are lawful if no intention to discriminate; job or departmental systems are not seen as “bona fide”, plant or company-wide systems are seen as “bona fide”.

Exemptions to TVII

Testing: Employer may give and act upon professionally developed ability tests if they are not used to discriminate on the basis of the protected factors.

Preferential Treatment: It is unlawful to interpret TVII as requiring preferential treatment of individuals of protected groups - reverse discrimination

National Security: Discrimination is permitted

Testing: Employer may give and act upon professionally developed ability tests if they are not used to discriminate on the basis of the protected factors.

Preferential Treatment: It is unlawful to interpret TVII as requiring preferential treatment of individuals of protected groups - reverse discrimination

National Security: Discrimination is permitted

Further TVII Issues

• Fetal Protection– Johnson Controls 1991: An employer’s

exclusion of fertile women, but not fertile men, could not be justified on grounds that the rule protected the woman’s reproductive capacity and the physical welfare of the fetus.

– The safety qualification is limited to those instances where sex or pregnancy presents danger to customers or third parties. A fetus is not a “third party” whose safety is essential to the operation of the employer’s business, and thus cannot be the basis of a BFOQ.

• Fetal Protection– Johnson Controls 1991: An employer’s

exclusion of fertile women, but not fertile men, could not be justified on grounds that the rule protected the woman’s reproductive capacity and the physical welfare of the fetus.

– The safety qualification is limited to those instances where sex or pregnancy presents danger to customers or third parties. A fetus is not a “third party” whose safety is essential to the operation of the employer’s business, and thus cannot be the basis of a BFOQ.

Title VII - Sexual Harassment

• Employer is liable

• Supervisor is liable

• Unwelcome sexual advances in exchange for a favorable employment condition - Quid pro quo

• Employer is liable

• Supervisor is liable

• Unwelcome sexual advances in exchange for a favorable employment condition - Quid pro quo

Sexual Harassment

• Hostile work environment sexual harassment– Pattern of behavior. – Policy and process. – Examples

• Onclae v. Sundowner --- allows employers to be sued by members of the same sex.

• Faragher v. Boca Raton --- ER liable even if the employer had no knowledge of the harassment.

• Burlington v. Ellerth --- allows employers to be sued for quid pro quo even if the employee suffered no tangible loss of job benefits for declining the supervisor’s sexual advances

• Hostile work environment sexual harassment– Pattern of behavior. – Policy and process. – Examples

• Onclae v. Sundowner --- allows employers to be sued by members of the same sex.

• Faragher v. Boca Raton --- ER liable even if the employer had no knowledge of the harassment.

• Burlington v. Ellerth --- allows employers to be sued for quid pro quo even if the employee suffered no tangible loss of job benefits for declining the supervisor’s sexual advances

Sexual Harassment

• Reading #1 – Three Pronged Approach – Typical SH Situation– Typical Victim– Two Responses

• Reactance – confrontational• Learned helplessness – passive and acquiescent

– Likely Response– Typical Remedy – Policy assumes which response?– Three pronged approach provides remedy considering the

typical victim• Org Communication – Zero tolerance; complaint process; third party• Involvement – Training of all employees; role playing; consequences• Proactive Actions – Investigation; implementation of consequences

• Reading #1 – Three Pronged Approach – Typical SH Situation– Typical Victim– Two Responses

• Reactance – confrontational• Learned helplessness – passive and acquiescent

– Likely Response– Typical Remedy – Policy assumes which response?– Three pronged approach provides remedy considering the

typical victim• Org Communication – Zero tolerance; complaint process; third party• Involvement – Training of all employees; role playing; consequences• Proactive Actions – Investigation; implementation of consequences

Executive Order 11246

Contractors doing business with federal government ($ amount of contract specified).

Same provisions as TVII AND requires contractors to develop affirmative action plans: Formal, specific personnel programs that are designed to increase the participation of protected groups.

1967 … sex-based discrimination added as prohibited

Contractors doing business with federal government ($ amount of contract specified).

Same provisions as TVII AND requires contractors to develop affirmative action plans: Formal, specific personnel programs that are designed to increase the participation of protected groups.

1967 … sex-based discrimination added as prohibited

Age Discrimination in Employment Act 1967

• Amended 1986. Protects EEs and applicants who are 40 years old and above (no upper limit).

• No mandatory retirement age (except law enforcement officers, firefighters, tenured professors, executive under certain conditions, top policy makers.);

• No reverse discrimination.

• Amended 1986. Protects EEs and applicants who are 40 years old and above (no upper limit).

• No mandatory retirement age (except law enforcement officers, firefighters, tenured professors, executive under certain conditions, top policy makers.);

• No reverse discrimination.

Americans with Disabilities Act 1990

• Since 1994 covers Ers with 15 or more Ees.

• 43 mill. Disabled Americans.• Protects:

• Physical or mental impairment that substantially limits one or more life activities (walk, see, ..)

• Record of impairment• Regarded as having impairment

• … about 1,000 disabilities (affective disorders, biochemically based disorders - AIDS, Cancer, Anxiety Disorders, Eating Disorders, Infertility, Epilepsy)

• Disability evaluated with adjustive equipment (glasses)

• Since 1994 covers Ers with 15 or more Ees.

• 43 mill. Disabled Americans.• Protects:

• Physical or mental impairment that substantially limits one or more life activities (walk, see, ..)

• Record of impairment• Regarded as having impairment

• … about 1,000 disabilities (affective disorders, biochemically based disorders - AIDS, Cancer, Anxiety Disorders, Eating Disorders, Infertility, Epilepsy)

• Disability evaluated with adjustive equipment (glasses)

ADA

• How it protects• Punitive damages• Essential job functions• Reasonable accommodations• Restructuring of physical facilities• Perceptual restructuring

• … 1994 5,500 complaints (25% more than were expected)

• How it protects• Punitive damages• Essential job functions• Reasonable accommodations• Restructuring of physical facilities• Perceptual restructuring

• … 1994 5,500 complaints (25% more than were expected)

ADA

• … cultural change; education vs compliance

• … “Be reasonable, thoughtful, caring, and you can comply” – Janet Reno

• … cultural change; education vs compliance

• … “Be reasonable, thoughtful, caring, and you can comply” – Janet Reno

Other Laws

• Rehabilitation Act 1972

• Vietnam Era Readjustment Act 1974

• Rehabilitation Act 1972

• Vietnam Era Readjustment Act 1974

Family and Medical Leave Act 1993

Employers with more than 50 employees have to provide 12 weeks of unpaid leave for family or medical emergencies.

Employer must guarantee the employee the same or a comparable job.

The employer must also pay the health-care coverage for the EE --- which the EE has to be back if he/she fails to return to work.

ERs are allowed to exempt “key” employees – defined as the highest paid 10% of their work force whose leave would cause substantial economic harm to the employer. Also exempt are EEs who have not worked at least 1,250 hours (25 hrs a week) in the previous 12 months.

Employers with more than 50 employees have to provide 12 weeks of unpaid leave for family or medical emergencies.

Employer must guarantee the employee the same or a comparable job.

The employer must also pay the health-care coverage for the EE --- which the EE has to be back if he/she fails to return to work.

ERs are allowed to exempt “key” employees – defined as the highest paid 10% of their work force whose leave would cause substantial economic harm to the employer. Also exempt are EEs who have not worked at least 1,250 hours (25 hrs a week) in the previous 12 months.

Enforcement of Laws and Court Process

• Filing a Discrimination Complaint– Local EEO Agency– NERC (Nevada Civil Rights Commission)– EEOC– Investigation– Right to sue letter

• Filing a Discrimination Complaint– Local EEO Agency– NERC (Nevada Civil Rights Commission)– EEOC– Investigation– Right to sue letter

Evidence of Discrimination

• Intentional Discrimination

• Disparate Treatment: different standards applied to various groups

• Adverse Impact: same standards are applied but disproportionately less minority applicants are selected

• Intentional Discrimination

• Disparate Treatment: different standards applied to various groups

• Adverse Impact: same standards are applied but disproportionately less minority applicants are selected

Federal Court Process

PRESENTATION OF EVIDENCE IN TITLE VII CASES

Burden of ProofPlaintiff Defendant Plaintiff

Prima Facie Evidence• 1. Disparate Treatment Job-based/legitimate Pretext

McDonnell Rule: 4 conditions explanation

• 2. Adverse Impact Business Necessity, 2. Other BFOQ, Validation method

80% or 4/5 Rule

PRESENTATION OF EVIDENCE IN TITLE VII CASES

Burden of ProofPlaintiff Defendant Plaintiff

Prima Facie Evidence• 1. Disparate Treatment Job-based/legitimate Pretext

McDonnell Rule: 4 conditions explanation

• 2. Adverse Impact Business Necessity, 2. Other BFOQ, Validation method

80% or 4/5 Rule

Disparate Treatment 4 Conditions- McDonnel Rule

Green vs McDonnel Douglas

• Plaintiff must show1. belongs to protected class

2. applied and was qualified for the job

3. despite the qualifications - was rejected

4. position remained open and the employer continued to seek applications from persons with the complainant’s qualifications

Applied also for ADEA cases

• Plaintiff must show1. belongs to protected class

2. applied and was qualified for the job

3. despite the qualifications - was rejected

4. position remained open and the employer continued to seek applications from persons with the complainant’s qualifications

Applied also for ADEA cases

Adverse Impact: 80% or 4/5 Rule

• Selection Ratio:

Number of nonminority applicants selected

DIVIDED BY

Number of nonminority applicants applied

=

NonminorityNonminority selection ratio selection ratio


Number of nonminority applicants selected

DIVIDED BY

Number of nonminority applicants applied

=

NonminorityNonminority selection ratio selection ratio

Adverse Impact: 80% or 4/5 Rule


Number of minority applicants selectedDIVIDED BY

Number of minority applicants applied

=

Minority Minority selection ratioselection ratio


Number of minority applicants selectedDIVIDED BY

Number of minority applicants applied

=

Minority Minority selection ratioselection ratio

Adverse Impact

• Compare the two selection ratios

• If the ratio for nonminorities is smaller there may be evidence of discrimination

• If the ratio is less than 80% or 4/5 of the nonminority ratio, then there is evidence of adverse impact (because the difference in the ratios is statistically significant)

• Compare the two selection ratios

• If the ratio for nonminorities is smaller there may be evidence of discrimination

• If the ratio is less than 80% or 4/5 of the nonminority ratio, then there is evidence of adverse impact (because the difference in the ratios is statistically significant)

Adverse Impact - Example

• 100 White applicants– 20 of the White applicants are selected– 20:100 = .2 Nonminority Selection Ratio

• 100 African American applicants– 5 of the African Americans are selected– 5:100 = .05 Minority Selection Ratio

• .05 : .2 = .25 = 25% and does NOT meet the 80% rule!

• The minority selection ratio would have to be .16 to be 80% of the nonminority ratio

• 100 White applicants– 20 of the White applicants are selected– 20:100 = .2 Nonminority Selection Ratio

• 100 African American applicants– 5 of the African Americans are selected– 5:100 = .05 Minority Selection Ratio

• .05 : .2 = .25 = 25% and does NOT meet the 80% rule!

• The minority selection ratio would have to be .16 to be 80% of the nonminority ratio

General Statistical Evidence for Discrimination

Stock Statistics# of women managers in org.

DIVIDED BY

# of skilled women managers in the work force

Total # of managers in the org. DIVIDED BY

Total # of skilled managers in the work force

What is the relevant labor market? EEO 1 form

Stock Statistics# of women managers in org.

DIVIDED BY

# of skilled women managers in the work force

Total # of managers in the org. DIVIDED BY

Total # of skilled managers in the work force

What is the relevant labor market? EEO 1 form

Landmark Selection Cases

• Resulted in establishing burden of proof requirements

• Resulted in establishing burden of proof requirements

EEO Legislation - How effective?

• EEO Laws clearly address societal problems --- safeguarding fair treatment in employment of traditionally disadvantaged groups.

• Hire the most qualified applicant -- the role and effect of stereotypes

• Internalization v Compliance

• EEO Laws clearly address societal problems --- safeguarding fair treatment in employment of traditionally disadvantaged groups.

• Hire the most qualified applicant -- the role and effect of stereotypes

• Internalization v Compliance

Review

• Statutory Laws– Early Civil Rights Acts– Equal Pay Act– Title VII of CRA 1964

• Coverage• Who is protected?• How?• Pregnancy Discrimination Act 1978

• Statutory Laws– Early Civil Rights Acts– Equal Pay Act– Title VII of CRA 1964

• Coverage• Who is protected?• How?• Pregnancy Discrimination Act 1978

Review

– Exemptions: BFOQ, business necessity, seniority system, testing

– Preferential Treatment and Reverse Discrimination

– Fetal Protection

– Sexual Harassment

– Exemptions: BFOQ, business necessity, seniority system, testing

– Preferential Treatment and Reverse Discrimination

– Fetal Protection

– Sexual Harassment

Review

• BFOQ and SH Exercises/Scenarios

• Discrimination Cases

• Two Readings

SH and Torts

• BFOQ and SH Exercises/Scenarios

• Discrimination Cases

• Two Readings

SH and Torts

Measurement in Selection

Selection decisions are based on what information?

Purpose is to ……..


Purpose is to ……..

Measurement in Selection


1. Need information about both:

JD -> KSA’s required for the job

2. Purpose is to match the individual and the job

?? -> KSA’s of the individual

How can we mess up?1. Measure irrelevant KSA’s

2. Measure KSA’s inaccurately


1. Need information about both:

JD -> KSA’s required for the job

2. Purpose is to match the individual and the job

?? -> KSA’s of the individual

How can we mess up?1. Measure irrelevant KSA’s

2. Measure KSA’s inaccurately

How can we “accurately” capture applicants’ KSA’s?

• We must determine the type and level of KSA’s that applicants have.

• The assumption is that the higher the level of KSA’s, the higher will be the level of predicted performance.

• Level - Measurement - Quantification

• We must determine the type and level of KSA’s that applicants have.

• The assumption is that the higher the level of KSA’s, the higher will be the level of predicted performance.

• Level - Measurement - Quantification

Definition of Measurement

• Application of rules for assigning numbers to objects to represent quantities of attributes.

• So that the differences between applicant scores are due to actual differences in KSA’s.

• RulesSpecified algorithms to assign numbers (She is

a 10) – same results by different users;

• Application of rules for assigning numbers to objects to represent quantities of attributes.

• So that the differences between applicant scores are due to actual differences in KSA’s.

• RulesSpecified algorithms to assign numbers (She is

a 10) – same results by different users;

Measurement

Attributes to be measured

Physical and psychological

ExamplesIntangible ones must be inferred from

indicants of these objects.

Attributes to be measured

Physical and psychological

ExamplesIntangible ones must be inferred from

indicants of these objects.

Measurement

Predictors (KSAs)

Indicants of relevant attributes - predict criteriaMust be important to the job (job related) Must be measures of attributes that are

identified as critical to job success

Criterion

measure or definition of what is meant by employee success on the job; e.g., employee behaviors, attitudes, supervisor ratings

Predictors (KSAs)

Indicants of relevant attributes - predict criteriaMust be important to the job (job related) Must be measures of attributes that are

identified as critical to job success

Criterion

measure or definition of what is meant by employee success on the job; e.g., employee behaviors, attitudes, supervisor ratings

Measurement and Individual Differences

Measurement is prerequisite for any statistical analysis

How precisely can we measure – can we detect small differences Classification of success as “yes” or “no” OR

degree of success??

ScaleMeans by which individuals can be

distinguished on a specific variable

Measurement is prerequisite for any statistical analysis

How precisely can we measure – can we detect small differences Classification of success as “yes” or “no” OR

degree of success??

ScaleMeans by which individuals can be

distinguished on a specific variable

Scales

Nominal scale: Scale composed of mutually exclusive categories (sex, race, job class); the numbers are “labels”; only frequencies

Ordinal scale: Ranks objects (hi, lo); differences between numbers yield additional information but not on the magnitude of the differences among ranks; e.g., percentile (represents the proportion of persons taking a test who made below a given score – 70th percentile means that 70% scored lower and 30% scored higher; does not tell how much higher and lower)

Interval scale: Arbitrary – no absolute zero; interpretation of differences – 40 vs 80 points does not mean 2 times the level of skill; e.g., zero on a test for math skills does not mean that the individual has zero math skills

Ratio scale: physical measures (height) and counting; has absolute zero.

Nominal scale: Scale composed of mutually exclusive categories (sex, race, job class); the numbers are “labels”; only frequencies

Ordinal scale: Ranks objects (hi, lo); differences between numbers yield additional information but not on the magnitude of the differences among ranks; e.g., percentile (represents the proportion of persons taking a test who made below a given score – 70th percentile means that 70% scored lower and 30% scored higher; does not tell how much higher and lower)

Interval scale: Arbitrary – no absolute zero; interpretation of differences – 40 vs 80 points does not mean 2 times the level of skill; e.g., zero on a test for math skills does not mean that the individual has zero math skills

Ratio scale: physical measures (height) and counting; has absolute zero.

Groups

Answer the following questions

1. What are descriptive statistics? Purpose and examples?

2. Why do we look at both – the mean and SD?3. What is a correlation? In Selection, what do

we correlate?4. What does a correlation of.8 and a t-value of

7.44 tell us?5. What is a normal distribution?6. What is statistical significance – hypothesis

testing?

Answer the following questions

1. What are descriptive statistics? Purpose and examples?

2. Why do we look at both – the mean and SD?3. What is a correlation? In Selection, what do

we correlate?4. What does a correlation of.8 and a t-value of

7.44 tell us?5. What is a normal distribution?6. What is statistical significance – hypothesis

testing?

Standardization of Selection Measures

Definition Selection MeasureSystematic instrument, technique, or procedure for

assigning scores to a characteristic or attribute of an individual

Detect a true difference

Standardized ifContent – measures same information; Administration -

information collected the same way; Scoring – rules for scoring are pre-specified

Individual DifferencesApplying the scale, each applicant receives a score –

how do we interpret the scores? What do they mean?

Definition Selection MeasureSystematic instrument, technique, or procedure for

assigning scores to a characteristic or attribute of an individual

Detect a true difference

Standardized ifContent – measures same information; Administration -

information collected the same way; Scoring – rules for scoring are pre-specified

Individual DifferencesApplying the scale, each applicant receives a score –

how do we interpret the scores? What do they mean?

Understand your data

Central tendency

Mean

Mode – most often observed score

• Median – 50% of the scores are above and 50% are below this score

Central tendency

Mean

Mode – most often observed score

• Median – 50% of the scores are above and 50% are below this score


Frequency Distribution• How many times did we get each score?

• First understanding of what our sample (applicant pool looks like) – did applicants tend to score higher or lower or are scores evenly distributed?

Frequency distribution is a frame of reference to give meaning to scores.

Most characteristics are normally distributed – bell curve! That means that most applicants score around average (have an average level of the characteristic, a few have more and a few have less).

Frequency Distribution• How many times did we get each score?

• First understanding of what our sample (applicant pool looks like) – did applicants tend to score higher or lower or are scores evenly distributed?

Frequency distribution is a frame of reference to give meaning to scores.

Most characteristics are normally distributed – bell curve! That means that most applicants score around average (have an average level of the characteristic, a few have more and a few have less).


VariationMean of squares of the deviation scores

(variance) depends on the extent to which scores cluster together

The square root of the variance is the standard deviation – a large standard deviation means that the scores a widely spread around the mean, a small standard deviation means that the scores are clustered around the mean

VariationMean of squares of the deviation scores

(variance) depends on the extent to which scores cluster together

The square root of the variance is the standard deviation – a large standard deviation means that the scores a widely spread around the mean, a small standard deviation means that the scores are clustered around the mean


HistogramHistogram


FrequencyFrequency


SkewnessScores are symmetrically or

asymmetrically distributed around the mean;

If the scores are symmetrically distributed then the mean = median;

SkewnessScores are symmetrically or

asymmetrically distributed around the mean;

If the scores are symmetrically distributed then the mean = median;


The distribution is positively skewed if the mean is larger than the median;

Negatively skewed if the mean is smaller than the median.

The distribution is positively skewed if the mean is larger than the median;

Negatively skewed if the mean is smaller than the median.

Skewness

Skewness

• A distribution is skewed if one of its tails is longer than the other.

• The first distribution shown has a positive skew. This means that it has a long tail in the positive direction.

• The distribution below it has a negative skew since it has a long tail in the negative direction.

• A distribution is skewed if one of its tails is longer than the other.

• The first distribution shown has a positive skew. This means that it has a long tail in the positive direction.

• The distribution below it has a negative skew since it has a long tail in the negative direction.

http://davidmlane.com/hyperstat/A52864.html




Sample Data

Applicant Test A Score (max 50) Test B Score (max 30)

1 30 26

2 18 14

3 35 15

4 27 10

5 25 27

6 42 25

7 21 21

8 35 18

9 47 20

10 35 25


Descriptive Statistics

• Frequencies• Mean• Median• Mode• Range

• SD =

Descriptive Statistics

• Frequencies• Mean• Median• Mode• Range

• SD = 1

)(

n

squaredmeanxSum i

Assignment #1

• Purpose: Review of Statistical Concepts and Overview of Measurement Concepts

• Test A and Test B - measure the same KSA• Type of Data• Descriptive Statistics - Range A, Range B => SD for A

compared to B• Interval size for Test B and Test A • Normally distributed test scores VS our test results• Negatively or positively skewed? (32.5)• Significance t-test and p-value


• Test A and Test B - measure the same KSA• Type of Data• Descriptive Statistics - Range A, Range B => SD for A

compared to B• Interval size for Test B and Test A • Normally distributed test scores VS our test results• Negatively or positively skewed? (32.5)• Significance t-test and p-value

Stat Assignment #1

• Descriptive Statistics• Two employment tests with scores for 10

employees• Which test should be used? Which applicant

should be hired?• Determine the correlation between test scores

and performance. The magnitude and significance of the correlation are used to determine which test should be used.

• Descriptive Statistics• Two employment tests with scores for 10

employees• Which test should be used? Which applicant

should be hired?• Determine the correlation between test scores

and performance. The magnitude and significance of the correlation are used to determine which test should be used.

Are two variables related?

• Correlation

• Meaning

• Range between +1.00 and -1.00

r = ∑ZxZy) where ZX = Xi-mean

SD N

• Correlation

• Meaning

• Range between +1.00 and -1.00

r = ∑ZxZy) where ZX = Xi-mean

SD N

Is this a chance relationship?

• Statistical Significance

• Hypothesis Testing

• T-statistics

• Statistical Significance

• Hypothesis Testing

• T-statistics


Normal DistributionNormal Distribution

Probability Distributions

• In order to draw conclusions about the scores that applicants receive, we have to evaluate whether our results are statistically significant

• We want to make inferences (draw conclusions) from our sample about the population

• Statistical significant results are not random but are truly describing the population.

• In order to draw conclusions about the scores that applicants receive, we have to evaluate whether our results are statistically significant

• We want to make inferences (draw conclusions) from our sample about the population

• Statistical significant results are not random but are truly describing the population.

Probability Distributions

Probability distribution or probability density function – the normal distribution is a theoretical density function

It is symmetric if: mean=mode=median

Entire area under the curve = 1.00

Probability distribution or probability density function – the normal distribution is a theoretical density function

It is symmetric if: mean=mode=median

Entire area under the curve = 1.00

Normal Distribution

Standardized normal distribution mean = 0 and SD = 1

68% of the scores are within + and – 1 SD around the mean

Standardized normal distribution mean = 0 and SD = 1

68% of the scores are within + and – 1 SD around the mean

Normal Distribution

In selection we assume that most characteristics that we measure are normally distributed in the population – that means if we had an endless number of observations our frequency distribution would look like a normal curve

This is important because evaluating the statistical significance of what we are interested in (hypotheses testing) is based on the assumption of a normal distribution.

In selection we assume that most characteristics that we measure are normally distributed in the population – that means if we had an endless number of observations our frequency distribution would look like a normal curve

This is important because evaluating the statistical significance of what we are interested in (hypotheses testing) is based on the assumption of a normal distribution.

Normal Distribution

If we assume a normal distribution, we can calculate z-scores

that means we can transform our raw scores (the score that the applicants received) into a score “on the normal curve”

by deducting the mean from each raw score and dividing that number by the SD (this is called the Z score);

So for each raw score, we get a z score that is important because we can now more easily

calculate other statistics such as correlations

If we assume a normal distribution, we can calculate z-scores

that means we can transform our raw scores (the score that the applicants received) into a score “on the normal curve”

by deducting the mean from each raw score and dividing that number by the SD (this is called the Z score);

So for each raw score, we get a z score that is important because we can now more easily

calculate other statistics such as correlations

Hypothesis Testing

• In order to draw valid conclusions from our sample, we must show that our results are statistically significant and not random

• We would like to reject the null hypothesis which says that our results are not truly reflecting the population

• For example: We want to conclude that the correlation between test scores and performance that we calculated for our sample is “true”

• Null Hypothesis: rxy = 0 which means that there is no relationship between x (test scores) and y (performance score).

• In order to draw valid conclusions from our sample, we must show that our results are statistically significant and not random

• We would like to reject the null hypothesis which says that our results are not truly reflecting the population

• For example: We want to conclude that the correlation between test scores and performance that we calculated for our sample is “true”

• Null Hypothesis: rxy = 0 which means that there is no relationship between x (test scores) and y (performance score).

Hypothesis Testing

• If H0 is true (no relationship) but we reject it, we make a Type I error which would be bad and we want to avoid it;

• Therefore, we allow only a minimum level of error in rejecting the H0 (traditionally .05 or .01 – this is your alpha level).

• Based on the observed correlation and the number of observations in our sample, we calculate a t-statistic. We then find the corresponding values, based on the sample size and the alpha level in the table for the t-distribution.

t= rxx

• If our obtained t-value is larger than the value in the table then our result is significant and we can reject the notion that there is not really a relationship between the two variables.

• If H0 is true (no relationship) but we reject it, we make a Type I error which would be bad and we want to avoid it;

• Therefore, we allow only a minimum level of error in rejecting the H0 (traditionally .05 or .01 – this is your alpha level).

• Based on the observed correlation and the number of observations in our sample, we calculate a t-statistic. We then find the corresponding values, based on the sample size and the alpha level in the table for the t-distribution.

t= rxx

• If our obtained t-value is larger than the value in the table then our result is significant and we can reject the notion that there is not really a relationship between the two variables.

) rxxsquared1/()2( N

p-Value

• p-value for a sample outcome is the probability that the sample outcome could have been more extreme than the observed one

• Large p-values support H0 while small p-values support the alternative hypothesis.

• Compare the p-value to the specified alpha risk. If p < alpha then conclude H1 (significance)

• p-value for a sample outcome is the probability that the sample outcome could have been more extreme than the observed one

• Large p-values support H0 while small p-values support the alternative hypothesis.

• Compare the p-value to the specified alpha risk. If p < alpha then conclude H1 (significance)

Tests and Reference Sources

• Buros’s Mental Measurement Yearbooks

• The Mental Measurement Yearbooks Database

• Journals

• Buros’s Mental Measurement Yearbooks

• The Mental Measurement Yearbooks Database

• Journals

Review

• How do we evaluate whether two variables are related to each other?

• Why and how do we determine whether our result is statistically significant?

• Why do we need to evaluate the quality of our measures?

• What does it mean when a measure is reliable?

• Using the test-retest method, how do we assess whether a measure is reliable?

• What does a p-value of .02 imply?

• How do we evaluate whether two variables are related to each other?

• Why and how do we determine whether our result is statistically significant?

• Why do we need to evaluate the quality of our measures?

• What does it mean when a measure is reliable?

• Using the test-retest method, how do we assess whether a measure is reliable?

• What does a p-value of .02 imply?

Overlapping Normalcurves

• Compare the means• Compare the means

Quality of Measures - Reliability

• How well does my test measure KSAs?

• The scores obtained on a measure are X obtained = X true + X error

– If there was no error in the measure, every time we apply the measure to the same person, we should get the same score.

– A reliable measure is a consistent measure.

– The reliability of a measure reflects the measures consistency.

• How well does my test measure KSAs?

• The scores obtained on a measure are X obtained = X true + X error

– If there was no error in the measure, every time we apply the measure to the same person, we should get the same score.

– A reliable measure is a consistent measure.

– The reliability of a measure reflects the measures consistency.

Reliability

• Three methods to evaluate the reliability of a measure • Each method focuses on a different source of

measurement error. – Measurement error are those factors that impact the

obtained score but are not at all related to the attribute that is being measured.

• The methods1. Test-Retest Reliability2. Parallel or Equivalent Forms Reliability3. Internal Consistency Reliability

1. Split-Half and Odd-Even; Cronbach Alpha2. Spearman-Brown Adjustment

• Three methods to evaluate the reliability of a measure • Each method focuses on a different source of

measurement error. – Measurement error are those factors that impact the

obtained score but are not at all related to the attribute that is being measured.

• The methods1. Test-Retest Reliability2. Parallel or Equivalent Forms Reliability3. Internal Consistency Reliability

1. Split-Half and Odd-Even; Cronbach Alpha2. Spearman-Brown Adjustment

Spearman-Brown Formula to Correct a Split-Half Reliability Coefficient

measureselection

theof 2 and 1 Partsbetween n correlatio ther

lengthin increased test was the timesofnumber n

measureselection totalfor thet coefficien

yreliabilit half-split corrected ther

:

1)r-(n1

nrr

12

ttc

12

12

ttc

Where

Reliability of an Interview

• Inter-rater Reliability• Inter-rater Reliability

Reliability

The conclusion that a measure is reliable

can only be drawn if, and only if, the

reliability coefficient (a correlation

coefficient) is statistically significant (as

determined by a t-test).

The conclusion that a measure is reliable

can only be drawn if, and only if, the

reliability coefficient (a correlation

coefficient) is statistically significant (as

determined by a t-test).

Reliability

• Interpretation of the reliability coefficient

The reliability coefficient is equal to the correlation coefficient between the obtained and the true score squared page 141

Acceptable magnitude of reliability The standard error of measurement - is the amount of

error to be expected in an individual’s score.

We calculate the standard error of measurement as the SD of the sample multiplied by the square root of 1 minus the reliability

coefficient

• Interpretation of the reliability coefficient

The reliability coefficient is equal to the correlation coefficient between the obtained and the true score squared page 141

Acceptable magnitude of reliability The standard error of measurement - is the amount of

error to be expected in an individual’s score.

We calculate the standard error of measurement as the SD of the sample multiplied by the square root of 1 minus the reliability

coefficient

Standard Error of Measurement

X measure ofy reliabilit ther

X measureon score obtained ofdeviation standard the

X measurefor t measuremen oferror standard the

:Where

xxxmeas

xx

x

meas

r-1

Standard Error of Measurement

Important

The difference in the scores between two applicants is only significant if it is at least

two times the standard error of measurement.

ExampleThe standard error of measurement for a test is 1.5.

Candidate A scores 18, candidate B scores 24. Does candidate B really have more of the attribute that is being measured?

Important

The difference in the scores between two applicants is only significant if it is at least

two times the standard error of measurement.

ExampleThe standard error of measurement for a test is 1.5.

Candidate A scores 18, candidate B scores 24. Does candidate B really have more of the attribute that is being measured?

Assignment #1• Purpose: Review of Statistical Concepts and Overview of

Measurement Concepts• Test A (Minnesota Clerical 50) and Test B (Purdue

Clerical Aptitude 30) - measure the same KSA: Clerical Skills

• Type of Data• Descriptive Statistics

– Understand your data

• Interval size (5 groups) for Test B (10-27) and Test A (18-47) – Histogram

• Normally distributed test scores VS our test results• Negatively or positively skewed? • Relationship to performance

– Test A – correlation .9 t*=7.44 alpha .01 (N=15; 2.65)– Test B – correlation .55 t*=2.41 alpha .05 (N=15; 1.77)

• Hire #9, score 47


• Test A (Minnesota Clerical 50) and Test B (Purdue Clerical Aptitude 30) - measure the same KSA: Clerical Skills

• Type of Data• Descriptive Statistics

– Understand your data

• Interval size (5 groups) for Test B (10-27) and Test A (18-47) – Histogram

• Normally distributed test scores VS our test results• Negatively or positively skewed? • Relationship to performance

– Test A – correlation .9 t*=7.44 alpha .01 (N=15; 2.65)– Test B – correlation .55 t*=2.41 alpha .05 (N=15; 1.77)

• Hire #9, score 47

Assignment #2

• Service Repair Technician• Reliability of written test and interviews• Reliability of written test:

1. Test - Re-test – Reliability coefficient 1. Magnitude 2. Significance

2. Internal Consistency - Split Half1. Magnitude 2. Significance

• Reliability of interviews (Interrater reliability coefficients – evaluate magnitude and significance):

1. Supervisor wit technician - .48 at .052. Screening with supervisor – lowest .32 and NS 3. Screening with technician - .51 at .05

• SEM - which candidate to choose – Confidence intervals .05 – overlap – 2 times SEM? F=94; G=91

• Service Repair Technician• Reliability of written test and interviews• Reliability of written test:

1. Test - Re-test – Reliability coefficient 1. Magnitude 2. Significance

2. Internal Consistency - Split Half1. Magnitude 2. Significance

• Reliability of interviews (Interrater reliability coefficients – evaluate magnitude and significance):

1. Supervisor wit technician - .48 at .052. Screening with supervisor – lowest .32 and NS 3. Screening with technician - .51 at .05

• SEM - which candidate to choose – Confidence intervals .05 – overlap – 2 times SEM? F=94; G=91

Quality of Measures - Validity

• Validity in Selection concerns the following question:

How appropriate is it to make inferences from the scores on a measure to performance?

• Is the score a good predictor of performance? Is the score actually related to future performance?

• Relationship between reliability and validity

• Validity in Selection concerns the following question:

How appropriate is it to make inferences from the scores on a measure to performance?

• Is the score a good predictor of performance? Is the score actually related to future performance?

• Relationship between reliability and validity

Quantitative Relationship between Validity and Reliability

Yfor t coefficieny reliabilitr

Xpredictor for t coefficieny reliabilitr

t)coefficien

(validity Ycriterion and Xpredictor

between n correlatio possible maximum r

:Where

rrr

yy

xx

xy

yyxx xy

Validity

Three methods to evaluate the validity of a measure.

1. Content Validity

2. Construct Validity

3. Criterion-Related (Empirical) Validity– Predictive Validity– Concurrent Validity

Three methods to evaluate the validity of a measure.

1. Content Validity

2. Construct Validity

3. Criterion-Related (Empirical) Validity– Predictive Validity– Concurrent Validity

Major Steps in Conducting Concurrent Validation Studies

• Conduct analyses of the job

• Determine relevant KSAs and other characteristics required to perform the job successfully

• Choose or develop the experimental predictors of these KSAs.

• Conduct analyses of the job



Major Steps in Conducting Concurrent Validation Studies

• Select criteria of job success

• Administer predictors to current employees and collect criterion data

• Analyze predictor and criterion data


• Administer predictors to current employees and collect criterion data


Major Steps in Conducting Predictive Validation Studies

• Conduct Analyses of the job



• Conduct Analyses of the job



Major Steps in Conducting Predictive Validation Studies


• Administer predictors to job applicants and file results

• After passage of a suitable period of time, collect criterion data



• Administer predictors to job applicants and file results

• After passage of a suitable period of time, collect criterion data


Requirements for a Criterion-Related Validation Study

• The job should be reasonably stable and not in a period of change or transition

• A relevant, reliable criterion that is free from contamination must be available or feasible to develop

• The job should be reasonably stable and not in a period of change or transition

• A relevant, reliable criterion that is free from contamination must be available or feasible to develop

Requirements for a Criterion-Related Validation Study

• It must be possible to base the validation study on a sample of people and jobs that is representative of people and jobs to which the results will be generalized

• A large enough sample of people on whom both predictor and criterion data have been collected must be available

• It must be possible to base the validation study on a sample of people and jobs that is representative of people and jobs to which the results will be generalized

• A large enough sample of people on whom both predictor and criterion data have been collected must be available

Content versus Face Validity

Content Validity deals with the representative sampling of the content domain of a job by a selection measure

Face Validity concerns the appearance of whether a measure is measuring what is intended

Content Validity deals with the representative sampling of the content domain of a job by a selection measure

Face Validity concerns the appearance of whether a measure is measuring what is intended

Strategies for Selection Decision-Making

• How to transform DATA into relevant information– Data Collection– Data Combination

• Judgmental and Mechanical Methods• Selection Decision-Making Strategies

» Multiple Regression - Compensatory Model» Multiple Hurdle» Combination» Profile Matching

• How to transform DATA into relevant information– Data Collection– Data Combination

• Judgmental and Mechanical Methods• Selection Decision-Making Strategies

» Multiple Regression - Compensatory Model» Multiple Hurdle» Combination» Profile Matching

Regression Analysis

• Y = f(X) - linear relationship• Collect data on X and Y• Scatterplot• Estimate the equation that describes the linear

relationship between X and Y• Estimate in such a way so that the predictions that

are made for Y (based on X using the equation) contain a minimal amount of error

• Least Squares Estimates• beta = regression coefficient• The equation for estimation is Y = beta0 +beta1X1

• Y = f(X) - linear relationship• Collect data on X and Y• Scatterplot• Estimate the equation that describes the linear

relationship between X and Y• Estimate in such a way so that the predictions that

are made for Y (based on X using the equation) contain a minimal amount of error

• Least Squares Estimates• beta = regression coefficient• The equation for estimation is Y = beta0 +beta1X1

Example

• Assignment #3 - Multiple RegressionEmpirical Weights for Selection Devices

X1 = Mechanical Ability TestX2 = Supervisor InterviewX3 = Technician InterviewX4 = Initial Screening Interview

Y = beta + beta1 X1 + beta2 X2+beta3 X3 +beta4 X4

The weights reflect the extent to which each selection device contributes to explaining performance

Question: Is a compensatory model what we want?

• Assignment #3 - Multiple RegressionEmpirical Weights for Selection Devices

X1 = Mechanical Ability TestX2 = Supervisor InterviewX3 = Technician InterviewX4 = Initial Screening Interview

Y = beta + beta1 X1 + beta2 X2+beta3 X3 +beta4 X4

The weights reflect the extent to which each selection device contributes to explaining performance

Question: Is a compensatory model what we want?

Assignment #3

• Validation of several selection devices and interpretation and use of validity information

• Magnitude and Significance

• Variation explained

• Validity Coefficient for each predictor – Mechanical ability test .76– Validity coefficient squared indicates how much of the variation in

performance is explained by this predictor alone: .58% (.76*.76)

– Reliability: Best was mechanical ability test, then technician interview

• Validation of several selection devices and interpretation and use of validity information

• Magnitude and Significance

• Variation explained

• Validity Coefficient for each predictor – Mechanical ability test .76– Validity coefficient squared indicates how much of the variation in

performance is explained by this predictor alone: .58% (.76*.76)

– Reliability: Best was mechanical ability test, then technician interview

Major Steps for Implementing a Construct Validation Study

• The construct must be carefully defined and hypotheses formed concerning the relationships between the constructs and other variables

• A measure hypothesized to assess the construct is developed

• The construct must be carefully defined and hypotheses formed concerning the relationships between the constructs and other variables

• A measure hypothesized to assess the construct is developed

Major Steps for Implementing a Construct Validation Study

• Studies testing the hypothesized relationships between the construct measured and other, relevant variables are conducted.

• Studies testing the hypothesized relationships between the construct measured and other, relevant variables are conducted.

Major Factors Affecting the Size of Validity Coefficients

• Reliability of Criterion and Predictor

• Restriction of Range

• Criterion Contamination

• Reliability of Criterion and Predictor

• Restriction of Range

• Criterion Contamination

Validity

• Interpretation of Validity Coefficients

1. Magnitude and Significance2. Cross-validation3. Correction for attenuation4. Correction for Restriction of Range5. Criterion Contamination

• Interpretation of Validity Coefficients

1. Magnitude and Significance2. Cross-validation3. Correction for attenuation4. Correction for Restriction of Range5. Criterion Contamination

Utility Analysis

• Using dollar-and-cents terms as well as other measures – such as percentage increase in output,– it shows the degree to which the use of a selection

measure improves the quality of individuals selected

– over what would have happened if the measure had not been used.

• Using dollar-and-cents terms as well as other measures – such as percentage increase in output,– it shows the degree to which the use of a selection

measure improves the quality of individuals selected

– over what would have happened if the measure had not been used.

An Equation for Calculating the Utility of a Selection Program

Expected Dollar Gain from Selection=

NsrxySDyZx-NT(C)

Expected Dollar Gain from Selection=return in dollars to the organization for having a valid selection program

Expected Dollar Gain from Selection=

NsrxySDyZx-NT(C)

Expected Dollar Gain from Selection=return in dollars to the organization for having a valid selection program


Ns=number of job applicants selected

rxy=validity coefficient of the selection procedure

SDy=standard deviation of job performance in dollars

Ns=number of job applicants selected

rxy=validity coefficient of the selection procedure

SDy=standard deviation of job performance in dollars


Zx=average score on the selection procedure of those hired expressed in z or standardized score form as compared to the applicant pool

NT=number of applicants assessed with the selection procedure

C=cost of assessing each job applicant with the selection procedure

Zx=average score on the selection procedure of those hired expressed in z or standardized score form as compared to the applicant pool

NT=number of applicants assessed with the selection procedure

C=cost of assessing each job applicant with the selection procedure

Customer Service Skills Test

http://www.waldentesting.com/backup/salestests/custserv.htmhttp://www.waldentesting.com/backup/salestests/custserv.htm

Key Elements of Implementing a Content Validity Strategy

1. Conduct a comprehensive job analysis

2. Selection of experts participating in a content validity study – SME’s (subject matter expert)

3. Specification of selection measure content

4. Assessment of selection measure and job content relevance

1. Conduct a comprehensive job analysis

2. Selection of experts participating in a content validity study – SME’s (subject matter expert)

3. Specification of selection measure content

4. Assessment of selection measure and job content relevance

Content Validity

1. Task List – Relative importance2. KSA List – Relative importance3. KSA x Task Matrix4. Linkages – Strength5. Predictors6. Predictor x KSA Matrix7. Predictor Weights8. Integration of predictors

1. Task List – Relative importance2. KSA List – Relative importance3. KSA x Task Matrix4. Linkages – Strength5. Predictors6. Predictor x KSA Matrix7. Predictor Weights8. Integration of predictors

Example -- Server

• JA

=> Tasks

=> KSA Requirements

• Measures for KSA’s

• Content Validity??

• Selection Procedure

• JA

=> Tasks

=> KSA Requirements




WRIPAC – Content Validation

• Predict performance in Selection class

• Tasks?

• KSAs?

• Task x KSA Linkages?

• Predictors?

• Predictor x KSA Linkages?

• Selection Process

• Predict performance in Selection class

• Tasks?

• KSAs?

• Task x KSA Linkages?

• Predictors?

• Predictor x KSA Linkages?

• Selection Process

Designing a Selection Procedure

1. Job Analysis

2. Identification of relevant job performance dimensions

3. Identification of KSA’s necessary for the job

4. Development of assessment devices to measure KSA’s

5. Assessing the quality of the assessment devices - reliability and validity

6. Use of assessment devices

1. Job Analysis

2. Identification of relevant job performance dimensions

3. Identification of KSA’s necessary for the job

4. Development of assessment devices to measure KSA’s

5. Assessing the quality of the assessment devices - reliability and validity

6. Use of assessment devices

JA Reading

• What is JA? Define!• What is JA? Define!

Selection Methods Introduction

• For each method– To measure which KSA’s/Design– Adverse Impact– Validity

• For each method– To measure which KSA’s/Design– Adverse Impact– Validity

Application Forms and Resumes

• Introduction– Information about the applicant’s background and present

status -- brief and general OR long and detailed??– Based on .. Past behavior is a good predictor of future

behavior– To determine … minimum qualifications and general

suitability for job; permanent record;– Determine relative strengths and weaknesses– It is assumed that all data collected are used

• Training and Experience Requirements– Job-related training - formal and informal– Type of training; length; quality

• Introduction– Information about the applicant’s background and present

status -- brief and general OR long and detailed??– Based on .. Past behavior is a good predictor of future

behavior– To determine … minimum qualifications and general

suitability for job; permanent record;– Determine relative strengths and weaknesses– It is assumed that all data collected are used

• Training and Experience Requirements– Job-related training - formal and informal– Type of training; length; quality

Application Form ….

• Careful with degree requirements– Why?

• Certification requirements

• Careful with degree requirements– Why?

• Certification requirements

Application Blank

• Specific job-related experience and accomplishments– Minimum qualifications

• Maintained Filing System: YES NO• Used computer and Microsoft Word • TE Evaluation Form• Specific tasks are listed – indicate YES NO• For YES, describe experience

• Specific job-related experience and accomplishments– Minimum qualifications

• Maintained Filing System: YES NO• Used computer and Microsoft Word • TE Evaluation Form• Specific tasks are listed – indicate YES NO• For YES, describe experience

Application Blank

• Methods for collecting TE evaluation info– Holistic – general judgment about suitability p.433

– Point Method – A priori scale p.435

– Behavioral Consistency Method – Description of job behavior by ER and applicant p. 439

• Methods for collecting TE evaluation info– Holistic – general judgment about suitability p.433

– Point Method – A priori scale p.435

– Behavioral Consistency Method – Description of job behavior by ER and applicant p. 439

Application Blank

• Likely candidate for Adverse Impact -- Why?• Current forms -- 100% had at least 1 inappropriate question;

on average 7 inappropriate questions.• Are these questions acceptable? What do you really want to

know? – What was your maiden name?– What is your date of birth? What is your age?– What is your height and weight?– What language do you commonly use?– What is your religious faith?– List the number and ages of your children?– Do you have any physical or mental disabilites?– List your birthplace.– Have you ever been arrested?– Do you own your car/residence?

• Likely candidate for Adverse Impact -- Why?• Current forms -- 100% had at least 1 inappropriate question;

on average 7 inappropriate questions.• Are these questions acceptable? What do you really want to

know? – What was your maiden name?– What is your date of birth? What is your age?– What is your height and weight?– What language do you commonly use?– What is your religious faith?– List the number and ages of your children?– Do you have any physical or mental disabilites?– List your birthplace.– Have you ever been arrested?– Do you own your car/residence?

Application Forms ...

• Adverse Impact: High

• Validity: On average .1

• Select content – Job-related - Job-related language– Usefulness– Fairness -- Face Validity

• Adverse Impact: High

• Validity: On average .1

• Select content – Job-related - Job-related language– Usefulness– Fairness -- Face Validity

Validity of T&E Evaluation Methods (Schmidt and Hunter, 1998)

CriteriaPredictor Measure Overall J ob

PerformanceOverall perf.in Trainingprograms

T&E MethodBehavioralconsistency methodPoint Method

.45

.11NANA

Related MeasuresY ears of experienceY ears of education

.18

.10.01.20

CriteriaPredictor Measure Overall J ob

PerformanceOverall perf.in Trainingprograms

T&E MethodBehavioralconsistency methodPoint Method

.45

.11NANA

Related MeasuresY ears of experienceY ears of education

.18

.10.01.20

References and Recommendations

• To verify information

• Issues

• Assess applicant’s job experience

• Assess applicant’s effectiveness in those jobs -- what done and how well??

• Types of info received p.446

• To verify information

• Issues

• Assess applicant’s job experience

• Assess applicant’s effectiveness in those jobs -- what done and how well??

• Types of info received p.446

References

• Not appropriate to assess personality ..• Sources of and methods to collect Reference Data

– Methods: In-person; Mail p.448; Letter of R; Phone

– Sources: Former ER; Personal; Investigative agencies; Public record;

• Usefulness of reference data– Reliability: .4 or less

– Validity: .16-.26

– Reference giver-better if immediate supervisor

– Old and new jobs are very similar?

– Adverse Impact ??

• Not appropriate to assess personality ..• Sources of and methods to collect Reference Data

– Methods: In-person; Mail p.448; Letter of R; Phone

– Sources: Former ER; Personal; Investigative agencies; Public record;

• Usefulness of reference data– Reliability: .4 or less

– Validity: .16-.26

– Reference giver-better if immediate supervisor

– Old and new jobs are very similar?

– Adverse Impact ??

References ..

– Validity -- not much evidence -- favorable info -- job related

• better if content of the new and old job are very similar• low validity because low reliability and restricted range

– Recommendations • Don’t use subjective info• written consent by applicant• ask only specific job-related info• Development of reference checking system• Guidelines for defensible references page 426 and 427

– Validity -- not much evidence -- favorable info -- job related

• better if content of the new and old job are very similar• low validity because low reliability and restricted range

– Recommendations • Don’t use subjective info• written consent by applicant• ask only specific job-related info• Development of reference checking system• Guidelines for defensible references page 426 and 427

Application, resume, references

• Design – – Purpose– Which KSA’s?– Recommendations

• Adverse Impact?

• Validity?

• Design – – Purpose– Which KSA’s?– Recommendations

• Adverse Impact?

• Validity?

WAB

• Choose criterion

• Sample size

• As many predictors of HR outcomes as possible

• Regression => weights for items

• AI but can show validity

• Choose criterion

• Sample size

• As many predictors of HR outcomes as possible

• Regression => weights for items

• AI but can show validity

BIO Data

• Questions about personal background and life experiences

• Why?

• Questions about personal background and life experiences

• Why?

BIO Data

• Past behavior=> Future behavior• ACT• Autobiographical questions:

– academic achievement, – work attitudes, – self-perception, – feelings, – values, – educational experiences,– hobbies, – family relations, – use of leisure time,– early work experiences – -- focus on motivation??

• Past behavior=> Future behavior• ACT• Autobiographical questions:

– academic achievement, – work attitudes, – self-perception, – feelings, – values, – educational experiences,– hobbies, – family relations, – use of leisure time,– early work experiences – -- focus on motivation??

BIO Data

• Enhances info in AB

• Types of BIO data items– Hard vs soft p.487– Response type p.486

• Enhances info in AB

• Types of BIO data items– Hard vs soft p.487– Response type p.486

BIO Data

• BIO data are good predictors of job success (validity) and have less adverse impact on minorities than do many traditional tests;

• Face validity??? –

• BIO data are good predictors of job success (validity) and have less adverse impact on minorities than do many traditional tests;

• Face validity??? –

BIO Data

• Include as one of several predictors• Criteria: tenure; performance in training;

performance ratings; productivity • Mean validity coeff: .35; • Engineering .41; clerical .52; management .38;

sales .5• Must be based on JA and must be empirically

scored; reliable and accurate if verifiable

• Include as one of several predictors• Criteria: tenure; performance in training;

performance ratings; productivity • Mean validity coeff: .35; • Engineering .41; clerical .52; management .38;

sales .5• Must be based on JA and must be empirically

scored; reliable and accurate if verifiable

Developing BIO Data

STEPS IN CONSTRUCTION• Selecting a Job• Analyzing the Job and Defining the Criterion

Life History Domain• Forming Hypotheses of Life History

Experiences• Developing a Pool of Biodata Items• Prescreening and Pilot-Testing Biodata Items

STEPS IN CONSTRUCTION• Selecting a Job• Analyzing the Job and Defining the Criterion

Life History Domain• Forming Hypotheses of Life History

Experiences• Developing a Pool of Biodata Items• Prescreening and Pilot-Testing Biodata Items

Develop BIO Data for Professor in HR

??

Developing a Selection Procedure: Selection Process for Logistics Professor

• JA

• => Tasks

• => KSA Requirements




• JA

• => Tasks

• => KSA Requirements




Recent Study on BiodataPersonnel Psychology Volume 35 Issue 1, Pages 1 - 62 Published Online:

7 Dec 2006

VALIDITY AND FAIRNESS OF SOME ALTERNATIVE EMPLOYEE SELECTION PROCEDURES

RICHARD R. REILLY 1 GEORGIA T. CHAO 2

1 American Telephone & Telegraph Co. 2 Pennsylvania State University

ABSTRACTDespite extensive evidence that tests are valid for employee selection, Federal

Guidelines have urged employers to seek alternative selection procedures that are equally valid but have less adverse impact on minorities. Research on the validity, adverse impact and fairness of eight categories of alternatives was reviewed. Feasibility of operational use of each type of alternative in an employment setting was also discussed. Only biodata and peer evaluation were supported as having validities substantially equal to those for standardized tests. Previous reviews and more recent research indicated that interviews, self-assessments, reference checks, academic achievement, expert judgment and projective techniques had levels of validity generally below those reported for tests. Data, where available, offered no clear indication that any of the alternatives met the criterion of having equal validity with less adverse impact. Results are discussed and several additional promising alternatives are described.

Personnel Psychology Volume 35 Issue 1, Pages 1 - 62 Published Online: 7 Dec 2006

VALIDITY AND FAIRNESS OF SOME ALTERNATIVE EMPLOYEE SELECTION PROCEDURES

RICHARD R. REILLY 1 GEORGIA T. CHAO 2

1 American Telephone & Telegraph Co. 2 Pennsylvania State University

ABSTRACTDespite extensive evidence that tests are valid for employee selection, Federal

Guidelines have urged employers to seek alternative selection procedures that are equally valid but have less adverse impact on minorities. Research on the validity, adverse impact and fairness of eight categories of alternatives was reviewed. Feasibility of operational use of each type of alternative in an employment setting was also discussed. Only biodata and peer evaluation were supported as having validities substantially equal to those for standardized tests. Previous reviews and more recent research indicated that interviews, self-assessments, reference checks, academic achievement, expert judgment and projective techniques had levels of validity generally below those reported for tests. Data, where available, offered no clear indication that any of the alternatives met the criterion of having equal validity with less adverse impact. Results are discussed and several additional promising alternatives are described.

http://www3.interscience.wiley.com/journal/118503216/home

http://www3.interscience.wiley.com/journal/119559025/issue

http://www3.interscience.wiley.com/journal/118503216/home

http://www3.interscience.wiley.com/journal/119559025/issue

Employment Interview

• KSA’s to be measured

• Validity

• Adverse Impact

• KSA’s to be measured

• Validity

• Adverse Impact


• Characteristics and Purposed of the Selection Interview:

1. Dialogue, 2. Gather information 3. Evaluate qualifications

• Selection interview: varies in – type – content

• Characteristics and Purposed of the Selection Interview:

1. Dialogue, 2. Gather information 3. Evaluate qualifications

• Selection interview: varies in – type – content


• Problems with the interview– lacks standardization in questions and

evaluation– is not focused– is worker rather than job-content oriented– requires the interviewer to fulfill multiple

functions

• Interviews involve cognitive and social processes

– Information processing and decision-making– Interpersonal influences

• Problems with the interview– lacks standardization in questions and

evaluation– is not focused– is worker rather than job-content oriented– requires the interviewer to fulfill multiple

functions

• Interviews involve cognitive and social processes

– Information processing and decision-making– Interpersonal influences


• Research

• Interview does not add to selecting the most qualified candidate … because…..

• Research

• Interview does not add to selecting the most qualified candidate … because…..

Interview

Sources of problems

• impression formation

• human perception

Sources of problems

• impression formation

• human perception

Interview

Information processing and decision-making1. observe behaviors2. attribute to traits 3. impressions about applicant 4. depend on interviewer’s

1. knowledge structure, 2. a priori beliefs, 3. recall of information

E.g.: High GPA = Diligence, hard work; Competitive sport = Aggressiveness; PA = Social Skills

Information processing and decision-making1. observe behaviors2. attribute to traits 3. impressions about applicant 4. depend on interviewer’s

1. knowledge structure, 2. a priori beliefs, 3. recall of information

E.g.: High GPA = Diligence, hard work; Competitive sport = Aggressiveness; PA = Social Skills

Improve the Validity of the Interview

1. Decide on location and seating

2. More than one interviewer – Panel

3. KSA’s to be measured: interpersonal, communication skills

4. Job-related questions only - Multiple Questions (Behavioral)

5. Limit pre-interview info

6. Semi-structure

7. Use a rating format

8. Train the interviewer

1. Decide on location and seating

2. More than one interviewer – Panel

3. KSA’s to be measured: interpersonal, communication skills

4. Job-related questions only - Multiple Questions (Behavioral)

5. Limit pre-interview info

6. Semi-structure

7. Use a rating format

8. Train the interviewer

Interview Simulation

• Relevant Tasks• Relevant KSA’s - combine into categories or

dimensions• KSA’s to be measure in the interview• Linkage between Question and KSA• Quality of Questions• Interview Structure/ Process -

– 1. Measure interpersonal, communication skills– 2. Job-related questions only - Multiple Questions (Behavioral)– 3. Limit pre-interview info– 4. Use a panel– 5. Use a rating format– 6. Train the interviewer– 7. Semi-structure

• Relevant Tasks• Relevant KSA’s - combine into categories or

dimensions• KSA’s to be measure in the interview• Linkage between Question and KSA• Quality of Questions• Interview Structure/ Process -

– 1. Measure interpersonal, communication skills– 2. Job-related questions only - Multiple Questions (Behavioral)– 3. Limit pre-interview info– 4. Use a panel– 5. Use a rating format– 6. Train the interviewer– 7. Semi-structure

Interview Role Play

* Interview Process? Non-verbals? Bias?* What KSAs are being measured?* To what extent does the applicant possess the required KSAs?

Interviewers Interviewee

Drew, Adrian, Kevin Addie

Amanda, Stacey, Andrew

Sammy

Physical Attractiveness

What do you think??What do you think??

Introduction

• Review the role of physical attractiveness in employment selection.

• Physical attractiveness is more salient during periods of impression formation such as selection.

• Review the role of physical attractiveness in employment selection.

• Physical attractiveness is more salient during periods of impression formation such as selection.

Definition of Attractiveness

• Physical features– Hair– Nose

• The degree to which one’s facial image elicits favorable reactions from others

• High reliability

• Physical features– Hair– Nose

• The degree to which one’s facial image elicits favorable reactions from others

• High reliability

Impact of Attractiveness

• Attractive people have positive traits– Less attractive people have less positive

traits

• Attractive applicants are perceived to be more qualified for employment

• Organizations retain employees high in attractiveness and ability

• Attractive people have positive traits– Less attractive people have less positive

traits

• Attractive applicants are perceived to be more qualified for employment

• Organizations retain employees high in attractiveness and ability

Relationship between sex and physical attractiveness

• Women are evaluated more than men

• Gender-linked bias

• May have impact on equal employment opportunity

• Women are evaluated more than men

• Gender-linked bias

• May have impact on equal employment opportunity

Job Related Factors

• Type of job– Male applicants are preferred for masculine

occupations– Female applicants are preferred for feminine

occupations

• PA is generally an asset for men

• PA might be a handicap for women depending on a types of jobs

• Type of job– Male applicants are preferred for masculine

occupations– Female applicants are preferred for feminine

occupations

• PA is generally an asset for men

• PA might be a handicap for women depending on a types of jobs

Physical Attractiveness vs. Age Discrimination

• Older applicants are judged as less attractive as younger applicants

• Preference for the young is surrogate preference for the young

• Three negative explanations:– Older workers are less effective– Young hires = better return on investment– Preference for the PA

• Older applicants are judged as less attractive as younger applicants

• Preference for the young is surrogate preference for the young

• Three negative explanations:– Older workers are less effective– Young hires = better return on investment– Preference for the PA

Race vs. Physical Attractiveness

• No attention has been directed to race PA interactions

• Based on other research:– PA blacks are more desirable dates and

essay writers

• No attention has been directed to race PA interactions

• Based on other research:– PA blacks are more desirable dates and

essay writers

No real understanding if stereotype extends to non-white applicants

Performance ratings are affected by the race of the rater

Conceptual and methodological problems in Physical Attractiveness research

• Restriction in range in the measurement

• Control vs. generalizability

• Normative biases

• Magnitude of the physical attractiveness bias

• Restriction in range in the measurement

• Control vs. generalizability

• Normative biases

• Magnitude of the physical attractiveness bias

Implications for the Study of Physical Attractiveness

• Physical Attractiveness is related to some types of decisions

• Some crucial questions in regards to the relative magnitude of PA bias– Whether it functions differentially for women

as compared to men– Whites as compared to nonwhites– Whether age is a surrogate for PA

• Physical Attractiveness is related to some types of decisions

• Some crucial questions in regards to the relative magnitude of PA bias– Whether it functions differentially for women

as compared to men– Whites as compared to nonwhites– Whether age is a surrogate for PA

Ability Testing

• Testing – Definition• Types of tests

– Mental Ability Tests - Wonderlic– Mechanical Ability Tests - Bennett and McQuarrie– Physical Ability– Integrity Tests– Clerical Ability – Minnesota Test

• Job Relatedness• Adverse Impact• Validity

• Testing – Definition• Types of tests

– Mental Ability Tests - Wonderlic– Mechanical Ability Tests - Bennett and McQuarrie– Physical Ability– Integrity Tests– Clerical Ability – Minnesota Test

• Job Relatedness• Adverse Impact• Validity

Personality Assessment

• Methods - Design

• Job Relatedness

• Adverse Impact

• Validity

• Methods - Design

• Job Relatedness

• Adverse Impact

• Validity

Personality

• Personality refers to a person’s unique and relatively stable pattern of thoughts, feelings, and actions

• Personality is an interaction between biology and environment

– Genetic studies suggest heritability of personality– Other studies suggest learned components of

personality

• Personality refers to a person’s unique and relatively stable pattern of thoughts, feelings, and actions

• Personality is an interaction between biology and environment

– Genetic studies suggest heritability of personality– Other studies suggest learned components of

personality

Measures of Personality

• Interviews– Unstructured: “Tell me about yourself…”– Structured: Set list of questions

• Observation: Psychologist learns about personality by observing the person

• Objective tests: Self-inventories that involve paper and pencil tests

• Projective tests: Subjects reveal aspects of their personality when they talk about ambiguous stimuli

• Interviews– Unstructured: “Tell me about yourself…”– Structured: Set list of questions

• Observation: Psychologist learns about personality by observing the person

• Objective tests: Self-inventories that involve paper and pencil tests

• Projective tests: Subjects reveal aspects of their personality when they talk about ambiguous stimuli

Projective Tests

• Projection is an idea developed by Freud in which people are thought to reveal their true feelings and thoughts when describing ambiguous stimuli

• A projective test presents a series of ambiguous stimuli and asks that a subject describe each stimulus– The idea is that their verbal

descriptions will reveal key aspects of their personality

• Projection is an idea developed by Freud in which people are thought to reveal their true feelings and thoughts when describing ambiguous stimuli

• A projective test presents a series of ambiguous stimuli and asks that a subject describe each stimulus– The idea is that their verbal

descriptions will reveal key aspects of their personality

Specific Projective Tests

• Rorschach Test– Consists of 10 inkblots– Reliability and validity of this test is low

• Thematic Apperception Test (TAT)– TAT also consists of a series of

ambiguous figures

• Rorschach Test– Consists of 10 inkblots– Reliability and validity of this test is low

• Thematic Apperception Test (TAT)– TAT also consists of a series of

ambiguous figures

Personality Measurement Issues

• Objective self-report personality tests can be criticized on the basis of

– Deliberate deception and social desirability bias

• Can the test detect deception and attempts to enhance social desirability?

– Diagnostic difficulties: the test may not be sufficiently specific to allow for diagnosis

– Inappropriate use: when tests are used for purposes other than their designed use

• Objective self-report personality tests can be criticized on the basis of

– Deliberate deception and social desirability bias

• Can the test detect deception and attempts to enhance social desirability?

– Diagnostic difficulties: the test may not be sufficiently specific to allow for diagnosis

– Inappropriate use: when tests are used for purposes other than their designed use

Personality Traits

• Traits are relatively stable and consistent personal characteristics

• Trait personality theories suggest that a person can be described on the basis of some number of personality traits– Allport identified some 4,500 traits– Cattel used factor analysis to identify 30-35 basic

traits– Eysenck argued there are distinct traits in

personality• Extraversion/introversion• Neuroticism

• Traits are relatively stable and consistent personal characteristics

• Trait personality theories suggest that a person can be described on the basis of some number of personality traits– Allport identified some 4,500 traits– Cattel used factor analysis to identify 30-35 basic

traits– Eysenck argued there are distinct traits in

personality• Extraversion/introversion• Neuroticism

The “Big 5”

• Modern personality research argues for 5 basic personality traits (OCEAN)

• Openness: whether a person is open to new experiences

• Conscientiousness: whether a person is disciplined and responsible

• Extroversion: whether a person is sociable, outgoing and affectionate

• Agreeableness: whether a person is cooperative, trusting, and helpful

• Neuroticism/Emotional Stability: whether a person is unstable and prone to insecurity

• Modern personality research argues for 5 basic personality traits (OCEAN)

• Openness: whether a person is open to new experiences

• Conscientiousness: whether a person is disciplined and responsible

• Extroversion: whether a person is sociable, outgoing and affectionate

• Agreeableness: whether a person is cooperative, trusting, and helpful

• Neuroticism/Emotional Stability: whether a person is unstable and prone to insecurity

Overview of the Big “5”

Myers – Briggs Type Indicator

• Temperament Theory

• 16 Personality Types

• Temperament Theory

• 16 Personality Types

Four Dimensions of Personality Type

• How we interact with the world and where we direct our energy (E/I)

• The kind of information we naturally notice (S/N)

• How we make decisions (T/F)

• Whether we prefer to live in a more structured way or a more spontaneous way (J/P)

• How we interact with the world and where we direct our energy (E/I)

• The kind of information we naturally notice (S/N)

• How we make decisions (T/F)

• Whether we prefer to live in a more structured way or a more spontaneous way (J/P)

Extraversion IntroversionInterest Orientation

E IOuter world of actions,

objects, and people

Inner world of ideas and concepts

Sensing iNtuitionPerception

S NImmediate reality and

direct experience

Inferred meanings

and relationships

Thinking FeelingJudgment

T FReliability of logical order – cause and

effect

Priorities based on personal

importance and values

Judgment PerceptionEnvironment Orientation

J PJudging attitude – Control of

events and systematic planning

Spontaneity – Curious, awaiting

events and adapting to

them

Myers Briggs Dimensions of Temperament

• Extraversion / Introversion– Where do you get your energy - what “charges your batteries” .

• Sensing / Intuition– How do you gather information. Present / future, practical /

imaginative, details / patterns, sequential / random

• Thinking / Feeling– How do you make decisions ?

– Thinking/feeling, laws/circumstances, justice/mercy

• Judgment / Perception– How do you organize your environment– Planned / open ended, control / adapt, resolved / pending

• Extraversion / Introversion– Where do you get your energy - what “charges your batteries” .

• Sensing / Intuition– How do you gather information. Present / future, practical /

imaginative, details / patterns, sequential / random

• Thinking / Feeling– How do you make decisions ?

– Thinking/feeling, laws/circumstances, justice/mercy

• Judgment / Perception– How do you organize your environment

– Planned / open ended, control / adapt, resolved / pending

ISTJ“Take Your

Time and Do It Right”

ISFJ“On My Honor,

to Do My Duty…”

INFJ“Catalyst for

Positive Change”

INTJ“Competence + Independence =

Perfection”

ISTP“Doing the Best I Can With What

I’ve Got”

ISFP“It’s the Thought

That Counts”

INFP“Still Waters Run Deep”

INTP“Ingenious Problem Solvers”

ESTP“Let’s Get

Busy!”

ESFP“Don’t Worry, Be Happy”

ENFP“Anything’s Possible”

ENTP“Life’s

Entrepreneurs”

ESTJ“Taking Care of

Business”

ESFJ“What Can I Do

For You?”

ENFJ“The Public Relations Specialist”

ENTJ“Everything’s Fine – I’m in

Charge”

Abstract

ConceptualAnalytical

Structural Social

©EMERGENETICS, LLC

Expressiveness

The outward display of emotions toward others and

the world-at-large

The outward display of emotions toward others and

the world-at-large

First-thirdQuiet

Alone0-33 percentile

Second-thirdReserved Spontaneous34-66 percentile

Third-third Gregarious

Performer67-100 percentile

©EMERGENETICS, LLC

Assertiveness

The degree of energy invested in expressing thoughts, beliefs and feelings

The degree of energy invested in expressing thoughts, beliefs and feelings

First-thirdPeacekeeper

Amiable0-33 percentile

Second-thirdEasy Going Competitive

33-66 percentile

Third-third Driving Telling

67-100 percentile

©EMERGENETICS, LLC

The willingness toaccommodate the thoughts

and actions of others

The willingness toaccommodate the thoughts

and actions of others

Flexibility

Second-thirdStrongOpinions

Likes different point of view

34-66 percentile

Likesambiguity

67-100 percentile

Puts others’needs before self

Third-thirdLikes definedsituations

Likes control

0-33 percentile

First-third

©EMERGENETICS, LLC

Emotional Intelligence

• I/O psychologists have long been interested in the relationship between intelligence and success within the work environment

• In addition to the KSAs traditionally associated with task performance, success in today’s organizations may require a more personal configuration of individual competencies

• I/O psychologists have long been interested in the relationship between intelligence and success within the work environment

• In addition to the KSAs traditionally associated with task performance, success in today’s organizations may require a more personal configuration of individual competencies

Emotional Intelligence (cont.)

• Competencies - the recognition, regulation, and expression of moods is currently receiving considerable attention

• These competencies may be subsumed under the rubric of Emotional Intelligence (EI)

• Competencies - the recognition, regulation, and expression of moods is currently receiving considerable attention

• These competencies may be subsumed under the rubric of Emotional Intelligence (EI)

What is Emotional Intelligence?

• The ability to perceive accurately, appraise and express emotion

• The ability to access and/or generate feelings when they facilitate thought

• The ability to understand emotion and emotional knowledge

• The ability to regulate emotions to promote emotional and intellectual growth.

• The ability to perceive accurately, appraise and express emotion

• The ability to access and/or generate feelings when they facilitate thought

• The ability to understand emotion and emotional knowledge

• The ability to regulate emotions to promote emotional and intellectual growth.


• Goleman’s theory is specific to the domain of work performance

Working with Emotional Intelligence (1998)

• Goleman’s theory is specific to the domain of work performance

Working with Emotional Intelligence (1998)


• Goleman further separates his theory from that of others by asserting that EI competencies can be learned and emphasizes that the identification of these competencies can be used to predict work performance across a wide variety of organizational settings

• Goleman further separates his theory from that of others by asserting that EI competencies can be learned and emphasizes that the identification of these competencies can be used to predict work performance across a wide variety of organizational settings

Elements of Emotional Intelligence

1. Self-Awareness

2. Self-Management

3. Social Awareness

4. Relationship Management

1. Self-Awareness

2. Self-Management

3. Social Awareness

4. Relationship Management

Elements of Emotional Intelligence (cont.)

• The elements of EI can be categorized under two sets of competencies:– Personal Competencies– Social Competencies

• The elements of EI can be categorized under two sets of competencies:– Personal Competencies– Social Competencies


• Personal Competencies:– Self-Awareness: knowing one’s internal

states, preferences, resources, and intuitions

– Self-Management: managing one’s internal states, impulses, and resources

– Motivation: emotional tendencies that guide or facilitate reaching goals

• Personal Competencies:– Self-Awareness: knowing one’s internal

states, preferences, resources, and intuitions

– Self-Management: managing one’s internal states, impulses, and resources

– Motivation: emotional tendencies that guide or facilitate reaching goals


• Social Competencies:– Empathy: awareness of others’ feelings,

needs, and concerns– Social Skills: adeptness at inducing

desirable responses in others

• Social Competencies:– Empathy: awareness of others’ feelings,

needs, and concerns– Social Skills: adeptness at inducing

desirable responses in others

EI

So What?So What?

Emotional Intelligence in the Workplace

• The Emotional Competence Inventory 2.0 (ECI 2.0) assesses EI of individuals and organizations

• The Emotional Competence Inventory 2.0 (ECI 2.0) assesses EI of individuals and organizations

Supporting Research

• Applicants scoring high on EI were more likely to be considered for employment (Maynard, 2003)

• High EQ (EI) is a predictor of job success and high performance (Fox, 2000)

• Positive correlation between a high EQ and Organizational Commitment and Organizational Citizenship Behaviors (OCB - Nikolaou & Tsaousis, 2002)

• Negative correlation between a high EQ and reported level of stress at work (Nikolaou & Tsaousis, 2002)

• Applicants scoring high on EI were more likely to be considered for employment (Maynard, 2003)

• High EQ (EI) is a predictor of job success and high performance (Fox, 2000)

• Positive correlation between a high EQ and Organizational Commitment and Organizational Citizenship Behaviors (OCB - Nikolaou & Tsaousis, 2002)

• Negative correlation between a high EQ and reported level of stress at work (Nikolaou & Tsaousis, 2002)

Implications for HR Professionals

• Individuals with low EQ scores are more likely to respond negatively to aversive work events– Decreased productivity– Health concerns

• Individuals with low EQ scores are more likely to respond negatively to aversive work events– Decreased productivity– Health concerns

Integrity and Drug Tests

• Purpose

• Measurement

• Conditions and Issues

• Purpose

• Measurement

• Conditions and Issues

Selection Project

• CONTENT VALIDITY– Empirical Validation– Face Validity

• Job Analysis

• Matrices - Linkages

• KSA Measures - Appropriateness, Design

• Report - Completeness

• CONTENT VALIDITY– Empirical Validation– Face Validity

• Job Analysis

• Matrices - Linkages

• KSA Measures - Appropriateness, Design

• Report - Completeness

Specific Jobs - Examples

The No-Asshole Rule and Blink

Questions for No Asshole Rule (Robert Sutton):

1. What is the No asshole rule about?

2. Describe the behaviors that characterize an AH.

3. Explain how such behaviors can be detrimental to creating a productive workplace.

4. From a practical perspective, what advice does Sutton give for the implementation of the no AH rule? What are the implications for employee selection of the no AH rule? Be specific.

5. Make a list of “to do’s” for your classmates of how to deal with Ahs in the workplace.

Questions for No Asshole Rule (Robert Sutton):

1. What is the No asshole rule about?

2. Describe the behaviors that characterize an AH.

3. Explain how such behaviors can be detrimental to creating a productive workplace.

4. From a practical perspective, what advice does Sutton give for the implementation of the no AH rule? What are the implications for employee selection of the no AH rule? Be specific.

5. Make a list of “to do’s” for your classmates of how to deal with Ahs in the workplace.

The No-Asshole Rule and Blink

Questions for blink (Daniel Goleman):

• What is blink about?

• How can thinking that takes place so quickly be at all useful? Don't we make the best decisions when we take the time to carefully evaluate all available and relevant information?

• Relate the ideas presented in "blink" to the material that we covered in class.

• Does "blink" talk about when rapid cognition goes awry? Explain.

• What do you take away from "blink"? How will you apply what you have learned?

Questions for blink (Daniel Goleman):

• What is blink about?

• How can thinking that takes place so quickly be at all useful? Don't we make the best decisions when we take the time to carefully evaluate all available and relevant information?

• Relate the ideas presented in "blink" to the material that we covered in class.

• Does "blink" talk about when rapid cognition goes awry? Explain.

• What do you take away from "blink"? How will you apply what you have learned?


Individual effectiveness =

f(Ability,Motivation)


Individual effectiveness =

f(Ability,Motivation)


What we have learned

• HR and Organizational Effectiveness

• HRM and Employee Selection

1. External Environment

2. Principles

3. Specific Methods

• HR and Organizational Effectiveness

• HRM and Employee Selection

1. External Environment

2. Principles

3. Specific Methods

HR and Org. Effectiveness

Match

• Individuals (Knowledge, Skills, Abilities)

• with

• Jobs (Requirements and Rewards)

Match

• Individuals (Knowledge, Skills, Abilities)

• with

• Jobs (Requirements and Rewards)

The HRM Framework

The External Environment

EconomySocial

EnvironmentLabor Market

LegalEnvironment

Match

Individual*KSA’s*Needs

HR Activities:Recruitment,Selection,Training,Compensation,Labor relations Job

*KSA Requirements*Rewards

HR Outcomes:Job SatisfactionOrg.commitmentAttractionRetentionAttendancePerformance

The External Environment

EconomySocial

EnvironmentLabor Market

LegalEnvironment

Match

Individual*KSA’s*Needs

HR Activities:Recruitment,Selection,Training,Compensation,Labor relations Job

*KSA Requirements*Rewards

HR Outcomes:Job SatisfactionOrg.commitmentAttractionRetentionAttendancePerformance

Selection

Definition - Selection

The process of obtaining and using information about job applicants to determine who should be hired.

Focus here is on how to collect relevant info on applicants’ KSA’s.

• Final decision must be accurate and fair.

Definition - Selection

The process of obtaining and using information about job applicants to determine who should be hired.

Focus here is on how to collect relevant info on applicants’ KSA’s.

• Final decision must be accurate and fair.

Course Summary

• External Environment – The Labor Market – Generational Differences– Legal Environment

• Principles of Selection - Measurement– What do we measure?– Quality of Measures– Reliability– Validity

• Selection Methods - Which KSA’s? Design? Adverse Impact? Validity– Application Blank/T&E/Bio Data/References– Employment Interview– Ability Tests– Personality

• External Environment – The Labor Market – Generational Differences– Legal Environment

• Principles of Selection - Measurement– What do we measure?– Quality of Measures– Reliability– Validity

• Selection Methods - Which KSA’s? Design? Adverse Impact? Validity– Application Blank/T&E/Bio Data/References– Employment Interview– Ability Tests– Personality

Readings1. Dealing with Sexual Harassment in the Workplace

2. Tort Law - Legal Trends: The Risk of Intentional Torts

3. Too Good to Hire

4. The Interview: Expecting A Quick Decision

5. Physical Attractiveness and Selection Decision Making

6. Employee Selection: Will Intelligence and Conscientiousness do the Job

7. They don’t do it often but they do it well

8. Elusive Criterion of Fit in Human Resources Staffing Decisions

9. Seven common misconceptions about human resource practices

10. HR Professionals’ Beliefs/Knowledge of Assessment Techniques

11. Use of graphology

12. International look at selection

1. Dealing with Sexual Harassment in the Workplace

2. Tort Law - Legal Trends: The Risk of Intentional Torts

3. Too Good to Hire

4. The Interview: Expecting A Quick Decision

5. Physical Attractiveness and Selection Decision Making

6. Employee Selection: Will Intelligence and Conscientiousness do the Job

7. They don’t do it often but they do it well

8. Elusive Criterion of Fit in Human Resources Staffing Decisions

9. Seven common misconceptions about human resource practices

10. HR Professionals’ Beliefs/Knowledge of Assessment Techniques

11. Use of graphology

12. International look at selection

Employee Selection

THE ENDTHE END

Advanced Topics in HR Employee Selection and Staffing MGT 467/667 Dr. Yvonne Stedham MGT 467/667 Dr. Yvonne Stedham.

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