IP2: Social Regulation of Emotion and Conflict Resolution
Klaus Scherer, Benoit Bediou
Swiss Center for Affective Sciences
Motivation
Context ESF-ECRP Grant (IP2): Emotion regulation in conflict and conflict resolution
AimSubjective perception of (in)justice and its role in conflict and conflict resolution
Study 1Investigate the impact of entitlement on emotions and behavior in social interactions, focusing on negotiation
Literature review
Study
Perspectives
1
2
3
Literature review
Study
Perspectives
1
2
3
1. Justice / Fairness
2. Entitlement
3. Negotiation
1. Justice / Fairness
2. Entitlement
3. Negotiation
Literature review
Study
Perspectives
1
2
31. Background & Aim
2. Paradigm & Design
3. Results & Discussion
1. Background & Aim
2. Paradigm & Design
3. Results & Discussion
Injustice as expectation violation
« People experience injustice when there is a discrepancy between what they expect based on salient or appropriate normative distribution rule and what they obtain” (Greenberg & Cohen, 1982).
Values & Norms in distributive justice
Different values & norms (distributive justice)e.g. equality, equity, need (Deutsch 1975)
Inter-individual differencese.g. egalitarian, meritocratic, libertarian (Frohlich et al. 2004; Cappelen et al. 2007)
Dicator Game with joint production
Frohlich et al 2004
Equity (41%)
Equality (26%)
Selfish (19%)
Productiv
ity?
Productiv
ity?
Effort?Effort?Effort?Effort?
Productiv
ity?
Productiv
ity?
Values & Norms in distributive justice
Intra-individual variabilitye.g. Rodriguez-Lara & Moreno-Garrido WP2010
Self-serving biases e.g. Messick & Sentis 1979
Bargaining impassese.g. Thompson & Loewenstein 1992
Summary of previous findings
Context Framing as Buyer/Seller (Hoffman et al. 1994) Initial Ownership (Leliveld et al. 1998)
Entitlement Earning the position (Guth & Thietz 1986; Hoffman et
al. 1994, 1996; Schotter et al 1996; Schurter & Wilson 2007)
Earning the pie (Ruffle, 1998; Cherry, 2001; Cherry et al. 2002; Oxoby & Spraggon 2008)
Dicator Game with joint production
Frohlich et al 2004
Equity (41%)
Equality (26%)
Selfish (19%)
Productiv
ity?
Productiv
ity?
Effort?Effort?Effort?Effort?
Productiv
ity?
Productiv
ity?
Paradigm & Design
Production: mental calculation (effort + skills) Distribution: negotiation (Ultimatum Game)
20 CHF
Player A Player B
Production screen
4 + 8 + 2 + 9
23
20 CHF
Player A Player B
Production screen
4 + 8 + 2 + 9
23
20 CHF
A B
Distribution – Proposer screen
A B
PRODUCTION DISTRIBUTIONX CHF 20-X CHF
20 CHF
A B
Distribution – Responder screen
A B
PRODUCTION DISTRIBUTION7 CHF 13 CHF
Accept
7/13Reject
0/0
Paradigm & Design
2 x 4 design Production: better, worse (than other player) Distribution: proposer; equity, equality, unfair
Measures Decisions: P’s offers and R’s decisions R’s judgments of satisfaction (and fairness)
Experiment design & predictions
DISTRIBUTION
PRODUCTION
N=33
Room A Room B
Room A Room B
Proposer – % Offered%
OFFER
ED
to R
esp
on
der
% PRODUCED by Responder
Proposer – % Offered%
OFFER
ED
to R
esp
on
der
% PRODUCED by Responder
R=0.35; p<0.01
Equity? Equality?
Proposer – % OfferedO
FFER
ED
to R
esp
on
der
(%
tota
l)
PRODUCED by Responder (% total)
Equit
y
Equality
Selfish
Proposer – % Kept
% PRODUCED by Proposer
% K
EP
T b
y P
rop
oser
Equit
y
Equality
Equality? Equity?Selfish
Equality rule?
<50% >50%
% K
ep
t
% Produced
Equality
*NS
Equity rule?
*
*Equit
y
% Produced
<50% >50%
% K
ep
t -
% P
rod
uced
Responder – Accept decision (188 obs)
<50% >50%
Offer: F(2,181)=109.88, p<0.001
% Produced
Fre
qu
en
cy
Responder – Satisfaction (N=27)
Offer: F(2,16)=67.79, p<0.001Production * Offer: F(2,32)=15.83,
p<0.001
Sati
sfa
cti
on
<50% >50%% Produced
Responder – Fairness (N=12)Fair
ness
<50% >50%% Produced
Fairness vs Satisfaction (72 obs)
Fairness
Sati
sfa
cti
on
Fairness
Conclusion
Individuals perceive and apply fairness norms flexibly depending on the context
Selfish bias due to biased entitlement/expectations? Low production => equality
Own effort > Other productivity High production => equity with generous adjustment
to avoid rejection Own productivity > other effort?
Strategic use of perspective taking to adapt offers to conflicting entitlement/expectations
Literature review
Study
Perspectives
1
2
31. Background & Aim
2. Feedback & Discussion
1. Background & Aim
2. Feedback & Discussion
Social Regulation of Emotion?
Injustice and Emotions e.g. Mikula et al. 1998; Weiss & Cropanzano 1996
1. Impact of norms violations on emotions?
Social Regulation of Emotion?
Injustice and Emotions e.g. Mikula et al. 1998; Weiss & Cropanzano 1996
1. Impact of norms violations on emotions? Injustice as expectation violation
e.g. Bicchieri et al. 2008
2. Prediction error signal in the ACC?
Social Regulation of Emotion?
Injustice and Emotions e.g. Mikula et al. 1998; Weiss & Cropanzano 1996
1. Impact of norms violations on emotions? Injustice as expectation violation
e.g. Bicchieri et al. 2008
2. Prediction error signal in the ACC? Impact of third-party ADR (e.g. mediation, arbitrage)
e.g. Cason & Mui 1998; Yamamori et al. WP; Shram & Charness, ESA 2010
3. Can we modify expectationemotionbehavior?
Changing expectations in the UG
Study 1 shows that people’s norms are flexible Study 2 will seek to modify people’s norms 2 phases:
1. Induction
a) Production (quiz)
b) Distribution (3rd-party UG - responder)
2. Measure
c) Production (quiz)
d) Distribution (2nd-party UG - proposer)
PRODUCTION
DISTRIBUTION (Responder)
Accept/Reject + fairness
ratings
X3 low prod / X3 high prodNo Arb. (group IV)
2 (intra Low/High prod) * 4 (inter NoArb., Arb.Egalitarian, Arb.Meritocratic, Arb.Control)
PRODUCTION
DISTRIBUTION (proposer)
Offer+ self fairness
ratings
X1 low prod / X1 high prod
X3 low prod/X3 high prodEgalitarian (group I)
Meritocratic (group II)+CONTROL (group III)?
PRODUCTION
DISTRIBUTION (Responder)
Accept/Reject + fairness
ratings
X1 low prod/X1 high prod
PRODUCTION
DISTRIBUTION (Proposer)
Offer+ self fairness
ratings
BASELINE. Offers made by 2nd party (proposer)
BASELINE. Offers made by 2nd party (proposer)
INDUCTION. Offers made by neutral 3rd partyINDUCTION. Offers made by neutral 3rd party
1 MEASURE. Offers made by neutral 3rd partyMEASURE. Offers made by neutral 3rd party
2
1 MEASURE. Offers made by neutral 3rd partyMEASURE. Offers made by neutral 3rd party
2
Room A Room B
Room A Room B
The arbitration
Control condition: Two of the participants will be randomly chosen and brought to another room to generate the offers[In fact, they will make ratings (emotions + fairness) of pre-determined offers]
Options:
Other task? e.g. fake arbitration
Non social? e.g. a computer will randomly generate a proposal
No arbitration? e.g. use baseline (offers made by 2nd party) as control
Other idea?e.g. 3rd party Dictator, passive viewing?
The arbitrator
Third party: [One of the participants] is observing the production phase and will make a proposal to both agents about the [A fair?] division of the pie. You can Accept or Reject his offer and you will also rate their fairness of his offers. […] will be paid according to your ratings, so he has an incentive to make fair offers.
Options:
Give him a form of power? (expertise? Legitimacy? Other types of power?) e.g : An highly skilled and experienced arbitrator or mediator
Give him a « norm compliance » function? e.g. [Player XXX] will ensure optimun fairness
Give him a personnal goal? e.g. the arbitrator’s goal is to ensure that both of you are satisfied
Give him a name and/or a face? : e.g. Picture or (fake) webcam recording…
Different (participant) arbitrator in each round? (greater social influence)
Predictions
Arbitration (attribution) R’s Fairness/Satisfaction should be higher for (unfair) offers made by 3rd parties vs 2nd parties?(e.g. Blount 1995)
Conformity with primed norm Participant should follow the norm of the arbitrator(e.g. Cason & Mui 1998; Yamamori et al. WP; Shram & Charness, ESA 2010) Effects should be greater arbitrator’s whose
proposals are rated high on fairness P’s ratings of self-fairness should be greater if
conformed with abitrator’s norm,
Predictions
Arbitration (attribution) R’s Fairness/Satisfaction should be higher for (unfair) offers made by 3rd parties vs 2nd parties?(e.g. Blount 1995)
Conformity with primed norm Participant should follow the norm of the arbitrator(e.g. Cason & Mui 1998; Yamamori et al. WP; Shram & Charness, ESA 2010) Effects should be greater arbitrator’s whose
proposals are rated high on fairness P’s ratings of self-fairness should be greater if
conformed with abitrator’s norm,
Social modulation of appraisalSocial modulation of appraisal
Methodological considerations
1. Type of third party? One of the participants? Power? Legitimacy? Expert or peer? Same or different in each round? Other ideas: passive viewer, dictator?
Methodological considerations
2. Type of induction task(induction, priming, anchoring, conformity?)
Control arbitration condition?e.g. random norm, social or computer, nonexpert?
No arbitration? (anchoring, reference) Other idea: participants could be passively
observing UG rounds in which one or different P’s would (in)consistently use the same norm while their emotions would be recorded?
Methodological considerations
3. Other questions and suggestions Induction phase: Participant always Responder? Test phase: Participant always Proposer? Better (e.g. continuous) DV than R’s A/R decision? Playing for a group? Inclusion/Exclusion? Repeat interaction with same player? 3rd party could emphasize value vs norm? Games on aggression?
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