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Record W2991167099 · doi:10.1177/0044118x19887075

Ugandan Adolescents’ Descriptive Gender Stereotypes About Domestic and Recreational Activities, and Attitudes About Women

2019· article· en· W2991167099 on OpenAlexaff
Flóra Faragó, Natalie D. Eggum, Zhang Li

Bibliographic record

VenueYouth & Society · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicGender Roles and Identity Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRecreationDescriptive statisticsPsychologyThematic analysisStereotype (UML)Psychological interventionSocial psychologyDescriptive researchDevelopmental psychologyGender studiesQualitative researchSociologyPolitical science

Abstract

fetched live from OpenAlex

In Eastern Uganda, 201 adolescents aged 11- to 17-years old (48% girls; M age = 14.62) answered close- and open-ended questions about gender stereotypes of domestic and recreational activities and gender-role attitudes about women’s behavior, rights, and roles. Adolescents answered questions such as “who is more likely to . . .?” assessing descriptive stereotypes (i.e., stereotype knowledge) and questions such as “is it ok for women to . . .?” assessing prescriptive stereotypes (i.e., stereotype endorsement) about gender roles. Data were analyzed via descriptive statistics, correlations, and thematic coding. Findings indicate that Ugandan adolescents were fairly egalitarian in some domains (e.g., leisure and recreation) but were non-egalitarian in other domains (e.g., marital and domestic roles). Adolescents held a mix of gender-stereotyped and non-stereotyped views about domestic and recreational activities as well as attitudes about women. Findings present reasons for hope and for continued work toward gender equality in Uganda. Results may inform interventions that foster gender egalitarian attitudes in youth.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.569

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 studies0.0010.000
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 head0.029
GPT teacher head0.278
Teacher spread0.249 · 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 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

Citations13
Published2019
Admission routes1
Has abstractyes

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