Jump to ContentJump to Main Navigation
Simple Heuristics in a Social World$
Users without a subscription are not able to see the full content.

Ralph Hertwig, Ulrich Hoffrage, and ABC Research Group

Print publication date: 2012

Print ISBN-13: 9780195388435

Published to Oxford Scholarship Online: January 2013

DOI: 10.1093/acprof:oso/9780195388435.001.0001

Show Summary Details
Page of

PRINTED FROM OXFORD SCHOLARSHIP ONLINE (oxford.universitypressscholarship.com). (c) Copyright Oxford University Press, 2020. All Rights Reserved. An individual user may print out a PDF of a single chapter of a monograph in OSO for personal use. date: 30 November 2020

Fast Acceptance by Common Experience: Augmenting Schelling's Neighborhood Segregation Model With FACE-Recognition

Fast Acceptance by Common Experience: Augmenting Schelling's Neighborhood Segregation Model With FACE-Recognition

Chapter:
(p.225) 8 Fast Acceptance by Common Experience: Augmenting Schelling's Neighborhood Segregation Model With FACE-Recognition
Source:
Simple Heuristics in a Social World
Author(s):

Nathan Berg

Katarzyna Abramczuk

Ulrich Hoffrage

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780195388435.003.0008

Schelling (1969, 1971a,b, 1978) observed that macro-level patterns do not necessarily reflect micro-level intentions, desires or goals. In his classic model on neighborhood segregation, which initiated a large and influential literature, individuals with no desire to be segregated from those who belong to other social groups, nevertheless, wind up clustering with their own type. Most extensions of Schelling's model have replicated this result. There is an important mismatch, however, between theory and observation that has received relatively little attention. Whereas Schelling-inspired models typically predict large degrees of segregation starting from virtually any initial condition, the empirical literature documents considerable heterogeneity in measured levels of segregation. This chapter introduces a mechanism that can produce significantly higher levels of integration and, therefore, brings predicted distributions of segregation more in line with real-world observation. As in the classic Schelling model, agents in a simulated world want to stay or move to a new location depending on the proportion of neighbors they judge to be acceptable. In contrast to the classic model, however, agents' classifications of their neighbors as acceptable or not depend lexicographically on recognition first and group type (e.g., ethnic stereotyping) second. The FACE-recognition model nests classic Schelling: when agents have no recognition memory, judgments about the acceptability of a prospective neighbor rely solely on his or her group type (as in the Schelling model). A very small amount of recognition memory eventually leads to different classifications that, in turn, produce dramatic macro-level effects resulting in significantly higher levels of integration. A novel implication of the FACE-recognition model concerns the large potential impact of policy interventions that generate modest numbers of face-to-face encounters with members of other social groups. The model describes a new co-evolutionary process in which individual-level classifications of others and the macro-structure of the social environment jointly and substantively influence one another.

Keywords:   ethnic, discrimination, agent based, computational economics, stereotypes, recognition, lexicographic, noncompensatory, heuristic, urban economics, institutional design, social judgment

Oxford Scholarship Online requires a subscription or purchase to access the full text of books within the service. Public users can however freely search the site and view the abstracts and keywords for each book and chapter.

Please, subscribe or login to access full text content.

If you think you should have access to this title, please contact your librarian.

To troubleshoot, please check our FAQs , and if you can't find the answer there, please contact us .