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Record W2091758243 · doi:10.1177/0146167212447234

Social Comparisons in Novel Situations

2012· article· en· W2091758243 on OpenAlexaff
Penelope Lockwood, Sarah Shaughnessy, Jennifer L. Fortune, Man-On Tong

Bibliographic record

VenuePersonality and Social Psychology Bulletin · 2012
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologySocial psychologyTransition (genetics)Social comparison theory

Abstract

fetched live from OpenAlex

The authors propose that individuals transitioning to a novel environment will prefer upward comparisons, particularly those made with individuals who have experienced a similar transition. Such comparisons help to reduce uncertainty and demonstrate that future success is possible. Study 1 found that individuals facing transitions to unfamiliar situations seek upward comparisons as a result of their uncertainty. Study 2 demonstrated that individuals who perceive themselves to be making a significant life transition are especially motivated by upward comparisons. Study 3 provided evidence that upward comparisons are especially inspiring to individuals making a transition to a novel cultural environment. Study 4 provided experimental evidence that individuals in a novel cultural environment are particularly inspired by upward comparisons with other newcomers. These studies suggest that upward comparisons with individuals who have experienced a similar transition enhance individuals' sense of control over future outcomes and play a key role during adjustment to novel environments.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.004
Scholarly communication0.0030.003
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.246
GPT teacher head0.451
Teacher spread0.205 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations41
Published2012
Admission routes1
Has abstractyes

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