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Record W2554447696 · doi:10.5539/ijps.v8n4p121

Romantic Priming Effects on the Social Desirability and Hireability of Self-Promoting Women

2016· article· en· W2554447696 on OpenAlexvenueno aff
Samantha B. Douglas, Juanita M. Cole

Bibliographic record

VenueInternational Journal of Psychological Studies · 2016
Typearticle
Languageen
FieldPsychology
TopicPersonality Traits and Psychology
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologySocial desirabilityPriming (agriculture)Social psychologyRomanceScale (ratio)

Abstract

fetched live from OpenAlex

The present study examined the effects of romantic and intelligence priming on the social-desirability and hireability of self-promoting and communal female job applicants. Participants were first primed with either romantic or intelligence related images and then asked to evaluate the social-desirability and hireability of three female job applicants. These job applicants were self-promoting and competent, communal and competent, or communal and not competent. After rating the job applicants, participants were reprimed and asked to complete a scale measuring career aspiration. Results revealed that participants rated the self-promoting applicant as more hirable than the communal applicants. In contrast, the communal and competent applicant was rated more socially desirable than the self-promoting applicant. No effect of priming on participants’ career aspiration or applicants’ social-desirability or hireability was found. However, there was a marginally significant relationship between participant gender and first choice to hire.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.120
GPT teacher head0.438
Teacher spread0.319 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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