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Record W3134475053 · doi:10.1080/14927713.2021.1886868

Examining gender roles in family leisure food provisions: a longitudinal photographic analysis

2021· article· en· W3134475053 on OpenAlexvenueno aff
Parisa Saadat Abadi Nasab, Trudie Walters, Neil Carr

Bibliographic record

VenueLeisure/Loisir · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologySociology

Abstract

fetched live from OpenAlex

The aim of this paper is to investigate how gender roles around family leisure food provisions have changed over time. To do this, family photographs depicting a variety of family leisure food provisions in New Zealand over the last 100 years were analyzed. Photographs are a useful lens for addressing such issues. They document aspects of lives that we may be unable to see easily via other sources. The photographs utilized in this study came from a combination of archival family photograph albums and more recent albums sourced privately through advertising and snowball sampling. They were analyzed using qualitative visual thematic analysis. The findings are categorized based on different leisure settings and show the nature of changes in gender in each setting over time. We found that despite social changes contributing to the empowerment of women, they still carry the main responsibility for the facilitation of food-related chores in the leisure experience. While men take the ‘frontstage glory’ of food preparation during family leisure occasions, women are shown either in the kitchen alone or looking after small children doing the ‘backstage work’.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.113
GPT teacher head0.307
Teacher spread0.193 · 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 designQualitative
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

Citations3
Published2021
Admission routes1
Has abstractyes

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