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Record W7074624283

Sexism and alexithymia: Correlations and differences as a function of gender, age, and educational level

2013· article· en· W7074624283 on OpenAlexaboutno aff

Bibliographic record

VenueRedalyc (Universidad Autónoma del Estado de México) · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicTheoretical and Computational Physics
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaAmbivalenceToronto Alexithymia ScaleCorrelationFunction (biology)Scale (ratio)
DOInot available

Abstract

fetched live from OpenAlex

The goals of the study were to analyze differences as a function of gender, age, and educational level in sexism and alexithymia in a nonclinical and in a clinical sample, and to explore the relation between these constructs. A descriptive and correlational cross-sectional methodology was used. The Ambivalent Sexism Inventory (Glick & Fiske, 1996) and the Toronto Alexithymia Scale (Parker et al. 1993) were administered. The sample comprised 989 participants from the Basque Country, aged between 18 and 65 years. The results revealed: 1) Significantly higher scores in the males in sexism (hostile, benevolent, and ambivalent) and in alexithymia (difficulties to express emotions and external-oriented thinking) in both samples; in the total alexithymia score, the males had significantly higher scores only in the nonclinical sample; 2) As of 55 years of age, a significant increase in benevolent and ambivalent sexism, and in difficulties to identify emotions, external-oriented thinking, and in the total alexithymia score were observed (only in the nonclinical sample); however, no changes with age were observed in hostile sexism and in difficulties to express emotions; 3) A decrease in sexism and alexithymia as the educational level increased; and 4) Significant positive correlations between sexism and alexithymia.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.511
Threshold uncertainty score0.502

Codex and Gemma teacher scores by category

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

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 head0.018
GPT teacher head0.229
Teacher spread0.211 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations6
Published2013
Admission routes1
Has abstractyes

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