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Record W3199695806 · doi:10.1177/01461672211042319

Two Ways to Stay at the Top: Prestige and Dominance Are Both Viable Strategies for Gaining and Maintaining Social Rank Over Time

2021· article· en· W3199695806 on OpenAlexaff
Kaylene J. McClanahan, Jon K. Maner, Joey T. Cheng

Bibliographic record

VenuePersonality and Social Psychology Bulletin · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsYork University
Fundersnot available
KeywordsDeferencePrestigeDominance (genetics)Social psychologyPsychologyNormativeRank (graph theory)Social statusDual (grammatical number)SociologyPolitical scienceSocial scienceMathematicsLawBiology

Abstract

fetched live from OpenAlex

The dual-strategies theory of social rank proposes that both dominance and prestige are effective strategies for gaining social rank (i.e., the capacity for influence) in groups. However, the only existing longitudinal investigation of these strategies suggests that, among undergraduate students, only prestige allows people to maintain social rank over time. The current study provides a longitudinal test of dominance and prestige in a context where dominance is more normative: MBA project groups. Among 548 MBA students in 104 groups, peer-rated dominance and prestige predicted gains in social rank over the course of 4 weeks, indicating that both strategies may help people not only gain social rank but also maintain it over time. Furthermore, prestige-but not dominance-led to social rank because of willingly given deference from group members. This confirms a central but thus-far-untested principle of dual-strategies theory: While prestige is based on freely conferred deference, dominance is not.

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, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.481
Threshold uncertainty score1.000

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 studies0.0030.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.051
GPT teacher head0.369
Teacher spread0.318 · 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 designNot applicable
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

Citations63
Published2021
Admission routes1
Has abstractyes

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