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Record W2057923599 · doi:10.1177/0146167213499377

Derailed by Diversity? Purpose Buffers the Relationship Between Ethnic Composition on Trains and Passenger Negative Mood

2013· article· en· W2057923599 on OpenAlexaff
Anthony L. Burrow, Patrick L. Hill

Bibliographic record

VenuePersonality and Social Psychology Bulletin · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsCarleton University
Fundersnot available
KeywordsPsychologyMoodEthnic groupSocial psychologyEthnic compositionDiversity (politics)Composition (language)Negative moodTrainSociologyGeographyArt

Abstract

fetched live from OpenAlex

Many individuals feel socially isolated and distressed in ethnically diverse settings. Purpose in life may buffer this form of distress by fostering one's sense of having a meaningful direction, which may also be of significance to others. In two experience-sampling studies with ethnically diverse participants, we examined associations between the ethnic composition of urban trains and passenger distress, and tested purpose as a moderator of these relationships. Study 1 showed that participants of all ethnic backgrounds reported greater negative mood when the percentage of ethnic out-group members aboard their train increased. However, individual differences in purpose significantly attenuated this effect. Study 2 replicated and extended these findings experimentally by showing that relative to a control condition, briefly writing about purpose prior to boarding trains also diminished the impact of ethnic composition on negative mood. The discussion addresses strategies for promoting positive adjustment in our increasingly diverse society.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.585
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.110
GPT teacher head0.374
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations68
Published2013
Admission routes1
Has abstractyes

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