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Record W2150633251 · doi:10.1080/10615800701330176

Psychological profiles and emotional regulation characteristics of women engaged in risk-taking sports

2007· article· en· W2150633251 on OpenAlexaboutno aff
N. Cazenave, Christine Le Scanff, Tim Woodman

Bibliographic record

VenueAnxiety Stress & Coping · 2007
Typearticle
Languageen
FieldPsychology
TopicAdventure Sports and Sensation Seeking
Canadian institutionsnot available
Fundersnot available
KeywordsSensation seekingAlexithymiaImpulsivityPsychologyBarratt Impulsiveness ScaleToronto Alexithymia ScaleClinical psychologyScale (ratio)Identity (music)Developmental psychologySocial psychologyPersonality

Abstract

fetched live from OpenAlex

We investigated the psychological profiles and emotional regulation characteristics of women involved in risk-taking sports. The research sample (N=180) consisted of three groups of women engaged in: (1) non-risk sports (N=90); (2) risk-taking sports for leisure purposes (N=53); or (3) risk-taking sports as professionals (N=37). Each participant completed five questionnaires, the Sensation Seeking Scale, the Bem Sex Role Inventory, the Barratt Impulsiveness Scale, Risk & Excitement Inventory, and the Toronto Alexithymia Scale. The results revealed significant differences between the groups' profiles. Of particular interest are the differences that exist between the profiles of Group 2 (escape profile, masculine gender identity, and high scores on sensation seeking, impulsivity, alexithymia) and Group 3 (compensation profile, androgynous gender identity, average score on sensation seeking, and low scores on impulsivity, alexithymia). We propose that the professional woman might be considered a model for preventing destructive risk-taking behaviors.

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)0.000
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
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 head0.027
GPT teacher head0.315
Teacher spread0.288 · 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

Citations87
Published2007
Admission routes1
Has abstractyes

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