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From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex
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From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

Dec 17, 2015

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Page 1: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

From mass panic to collective resilience: Understanding crowd behaviour in

emergencies and disasters

John Drury

University of Sussex

Page 2: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

From mass panic to collective resilience

AcknowledgementsSteve Reicher (St Andrews University)

Chris Cocking (London Metropolitan University)Damian Schofield, Paul Langston, Andy Burton (Nottingham University)

Andrew Hardwick (University of Sussex)

The research referred to in this presentation was made possible by a grant from the Economic and Social Research Council Ref. no: RES-000-23-0446

Page 3: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

‘Mass panic’

In the face of threat:–‘Instinct’ overwhelms socialization– Emotions outweigh reasoning– Rumours and sentiments spread uncritically through ‘contagion’– Reactions are disproportionate to the danger– Competitive and selfish behaviours predominate– Lack of co-ordination and disorder results– Grandmother trampled etc.

Page 4: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

But!

Panic is actually rare (Brown, 1965; Johnson, 1988;

Keating, 1982; Quarantelli, 1960).

Lack of mass panic:• Atomic bombing of Japan during World War II (Janis, 1951)

• Kings Cross Underground fire of 1987 (Donald & Canter, 1990)

• 9/11 World Trade Center disaster (Blake,

Galea, Westeng, & Dixon, 2004)

Page 5: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

• The concept of ‘mass panic’ persists in cognate disciplines, applied settings and popular representations

• Psychology has rejected ‘mass panic’

• Instead: models of crowd sociality

Page 6: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

Overview

• Models of mass emergency behaviour

• Explaining emergent sociality – social identity

• Case study

• Experimental study

• Comparative event study

• Implications – theory and practice

Page 7: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

The normative approach

Behaviour in emergencies is guided by everyday social roles and norms

E.g. Beverly Hills Supper Club fire (Johnson, 1988)

• evidence of mundane courtesy

• respect for the elderly

• gender roles maintained

Page 8: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

Affiliation

(i) In threat, we are motivated to seek the familiar rather than simply exit

(ii) The presence of familiar others (affiliates) has a calming effect, working against a ‘fight or flight’ reaction (Mawson, 2005)

E.g. Fire at the Summerland leisure complex in 1973. People tried to exit in small (family) groups, not alone (Sime, 1983)

Page 9: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

Advances on ‘mass panic’

Mass emergency behaviour as:

• Cognitive/ meaningful

• Social

From ‘vulnerability’ to ‘resilience’

Page 10: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

Problems

Normative approach: – Explanatory power of generic norms?– Risk to self as ‘normative’?

Affiliation:– Do crowds of strangers panic?– Helping strangers not just ‘affiliates’

Page 11: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

What kind of sociality?

Normative approach and affiliation:

pre-existing social bonds and/or interpersonal relationships as the basis of sociality in emergencies.

Social psychology: collective behaviour explained in terms of social identity

Page 12: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

A social identity approach to mass emergencies

Sociality: • Shared social identification: categorization

of self with others (rather than interpersonal bonds)

Emergence: • Shared fate is a possible criterion of shared

self-categorization (Turner, 1987)

• Shared experience in relation to threat/emergency creates sense of we-ness (Clarke, 2002)

Page 13: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

Applying social identity principles to mass emergency behaviour:

– reconnects the field with mainstream social psychology

– offers a new way of understanding ‘resilience’

Page 14: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

Case study

7th July 2005 London bombings(Cocking, Drury, & Reicher, in press)

Four bombs, 56 deaths, 700+ injuries.

Emergency services

didn’t reach all

the survivors

Immediately.

Page 15: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

Data

• Contemporaneous newspaper accounts: 141• Personal (archive) accounts: 127• Primary data: interviews and written e-mail

responses: 17

• Total: 146(+) witnesses, 90 of whom were survivors

• Material coded and counted

Page 16: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

Helping versus personal ‘selfishness’

(Helping: giving reassurance, sharing water, pulling people from the wreckage, supporting people up as they evacuated)

Contemporaneous newspaper accounts

Archive personal accounts

Primary data: Interviews and e-mails

‘I helped’ 57 42 13 ‘I was helped’ 17 29 10 ‘I saw help’ 140 50 17+ ‘Selfish’ behaviours 3 11 4 Total

141

127

17

Page 17: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

‘I remember walking towards the stairs and at the top of the stairs there was a guy coming from the other direction. I remember him kind of gesturing; kind of politely that I should go in front- ‘you first’ that. And I was struck I thought, God even in a situation like this someone has kind of got manners, really.’

(LB 11)

Page 18: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

Accounting for help

Contemporaneous newspaper accounts

Archive personal accounts

Primary data: Interviews and e-mails

Possibility of death 70 68 12 Not going to die - 2 1 With strangers - 57 15 With affiliates - 8 4 Total

141

127

17

Page 19: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

Accounting for help

Contemporaneous newspaper accounts

Archive personal accounts

Primary data: Interviews and e-mails

Shared fate 0 11 5 Unity 7 20 11 Disunity 0 0 1 Total

141

127

17

Page 20: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

‘unity’, ‘together’, ‘similarity’, ‘affinity’, ‘part of a group’, ‘everybody, didn’t matter what colour or nationality’, ‘you thought these people knew each other’, ‘teamness’[sic] ‘warmness’, ‘vague solidity’, ‘empathy’

Int: “can you say how much unity there was on a scale of one to ten?”

LB 1: “I’d say it was very high I’d say it was seven or eight out of ten.”

Int: “Ok and comparing to before the blast happened what do you think the unity was like before?”

LB 1: “I’d say very low- three out of ten, I mean you don’t really think about unity in a normal train journey, it just doesn’t happen you just want to get from A to B, get a seat maybe”

(LB 1)

• Almost all who referred to shared fate referred to unity

• Almost all who referred to unity referred to help

Page 21: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

Case study - conclusions

• Little evidence for ‘mass panic’

• Little support for affiliation

• Some support for social identity approach – shared threat enhances unity enhances co-operation

• Unplanned, uncontrolled study

• Need more data on identification

Page 22: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

Experimental analogues

Rationale: • To manipulate (not simply measure) identification• To take behavoural (not just self-report)

measures

Detour: The need for a new experimental design• Threat (distress) versus ethics• Aids to imagination

Page 23: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.
Page 24: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.
Page 25: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.
Page 26: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

Hi-identification (N = 20)

‘You have just been to an England football match at Wembley Stadium and are now on your way back to Brighton as you have university in the morning. You and the other England supporters are making your way through the local rail station to the Underground, from where you can get the train back home.

Lo-identification (N = 20)

‘You have spent a long day shopping in central London and are now on the way back to Brighton as you have university in the morning. You are making your way through the local rail station to the Underground, from where you can get the train back home.’

Page 27: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

‘You are just about to board the underground train when you hear someone shout “There’s a fire, get out, get out!” You look behind you and see large flames at one end of the platform with people running away from the fire. Everybody around you looks scared, and you feel yourself starting to sweat and sense your heart pumping faster. The fire seems to be getting bigger rapidly and you start to choke on the smoke. You realise that you may only have a few minutes to get back up to ground level and away from the fire in order to survive.’

• Hi-identification: ‘But there are other people trying to get out too…The station is still packed with other supporters…’

• Lo-identification: ‘But there are other people trying to get out too…The station is still packed…’

Page 28: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

Behavioural measures

• More help offered when danger was low (M = 1.30) than high (M = 1.05), F(1, 38) = 3.23, p = 0.08, ή = 0.08)

• More help offered in hi- (M = 0.70) than lo-identification (M = 0.48) condition (F(1, 40) = 6.42, p = 0.02, ή = 0.15)

• (No interaction)

• Greater pushing in lo- (M = 18.39) than hi-identification (M = 9.26) condition (F(1, 37) = 8.27, p = 0.0007, ή = 0.20)

Self-report measures

• Manipulation check – equal levels of engagement• Greater liking of others in hi-identification condition

Page 29: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

Experimental analogues - conclusions

• Some progress in developing a new experimental paradigm

• Some support for social identity

Ideally, we should combine:

• Control

• Ecological validity

Page 30: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

Comparative event study

Interviews with (21) survivors of (11) emergencies(Drury, Cocking, & Reicher, in press)

Sinking ships (Jupiter, 1988; Oceanos, 1991)

Harrods bomb (1983)

Hotel fire (1971)

Grantham train accident (2003)

Tower block evacuations (2001, 2002)

Bradford City fire (1985)

Fatboy Slim Brighton beach party (2002)

Ghana football stadium crush (2001)

Hillsborough crush (1989)

Page 31: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

• Step 1: Constructing comparisons

Low (n = 9) versus high (n = 12) identifiers

• Step 2: Origins of enhanced identification

Identification Low High Total ‘I felt in danger’ 56a 67 62 ‘Shared sense of danger’

67 92 80

a Figures are percentage of interviewees endorsing the statement, based on low-identification sample size of nine and high-identification sample size of 12.

Page 32: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

• Step 3: Comparing high and low identifiers on co-operation and selfishness

Identification Low High Total

‘Survivors helped others’ 78a (14) 83 (34) 81 (48) ‘Other survivors helped me’ 44 (6) 66 (14) 55 (20) ‘I helped other survivors’ 33 (7) 66 (14) 50 (21) ‘Other survivors were personally selfish to others’

44 (5)

33 (4)

39 (9)

‘Other survivors were personally selfish to me’

22 (2) 33 (5) 28 (7)

‘I was personally selfish to other survivors’

0 (0) 08 (1) 4 (1)

a Figures are percentage of interviewees endorsing the statement. (Figures in brackets indicate number of survivors the interviewee reported seeing or experiencing.)

Page 33: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

• Step 4: Comparing low and high identifiers on orderliness and disorderliness

Identification Low High Total

‘Order and calm’ 22a 42 32 ‘Control of emotions’ 33 42 38 ‘Mass panic’ 56 50 53 ‘Individual-only panic’ 44 83 64 ‘Everyday rules’ 33 67 50 ‘Normal roles’ 56 83 70 ‘Courtesy’ 11 25 18 ‘Discourtesy’ 11 0 6

a Figures are percentage of interviewees endorsing the statements.

Page 34: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

‘I don’t think people did lose control of their emotions

and I think the restraint shown by .. particularly several

of the.. individuals that I’ve mentioned I’ve talked

about .. it was the degree of the capacity of people to

help others who were clearly struggling, you know.. it’s it

should be source of great pride to those people I think. [

] I mean a lot of people were very.. as I was you know..

you’re being pushed, you’re being crushed when you’re

hot and bothered you’re beginning to fear for your own

personal safety and yet they were I think controlling or

tempering their emotions to help… try and remedy the

situation and help others who were clearly struggling’

(Hillsborough 2)

Page 35: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

Comparative event study - conclusions

• High-identification group more likely to report shared threat

• Those high in unity at the beginning reported increased unity over time

• Evidence of solidarity across the data-set – no ‘mass panic’

• However, solidarity was greater for the high-identification group

• Most solidarity involved strangers not affiliates

• Broadly in line with case study and experiments

Page 36: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

Implications - theoretical

This analysis in line with other approaches emphasizing that mass emergency behaviour is:

• Cognitive

• Social

Hence an emphasis on resilience rather than vulnerability

Page 37: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

‘Resilience’

• Individual psychology: a personal trait• Sociological accounts: emergency organizations

improvised co-ordination (9-11)

• Collective resilience: shared identification allows survivors to express and expect mutual solidarity and cohesion, and thereby to coordinate and draw upon collective sources of support and other practical resources, to deal with adversity

CR as the social-psychological basis of both individual resilience/recovery and organizational/structural resilience?

Page 38: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

Implications - practical

• Understanding the crowd as a resource not a problem

• Example – London bombs: survivors acted as fourth emergency service

• Catering for the public desire to help, allowing the public to be involved in its own protection

• Communication: Providing (not withholding) practical information

Page 39: From mass panic to collective resilience: Understanding crowd behaviour in emergencies and disasters John Drury University of Sussex.

If the image of mass panic is wrong

If crowd behaviour in emergencies is resilient (social, cognitive, resourceful)

Then the crowd is part of the solution in emergencies

And the discourse of ‘mass panic’ is part of the problem!