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Record W2943027563 · doi:10.1080/01490400.2019.1597792

#Family: Exploring the Display of Family and Family Leisure on Facebook and Instagram

2019· article· en· W2943027563 on OpenAlexaff
Charlene S. Shannon

Bibliographic record

VenueLeisure Sciences · 2019
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsNarrativeContext (archaeology)Construct (python library)Identity (music)PsychologyLeisure activityFamily lifeIdealizationSocial psychologyFace (sociological concept)Internet privacySociologyGender studiesComputer scienceAesthetics

Abstract

fetched live from OpenAlex

Family leisure is a context in which individuals construct identity and engage in activities considered “doing family.” Social networking sites (SNS) offer a modern tool for sharing photos and narratives and for constructing family identity and conveying it to others. The purpose of this study was to explore how family and family leisure are displayed through the practice of sharing family leisure photos on the SNSs Facebook and Instagram. Semi-structured, face-to-face interviews were conducted with 13 women, 3 men, and 1 gender fluid individual about their experiences with posting about activities or practices considered as “family leisure” on SNSs. The findings indicated that posted family leisure images and narratives were intended to communicate nonnormative definitions of family, clarify family identity, help individuals feel a sense of belonging within their social network and community and resist the typical idealization of family life, and offer authentic representations of family leisure.

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)0.001
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 score0.073
Threshold uncertainty score0.713

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.074
GPT teacher head0.320
Teacher spread0.246 · 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

Citations29
Published2019
Admission routes1
Has abstractyes

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