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Record W2902108345 · doi:10.1080/2159676x.2018.1550665

Single, Stay-at-Home, and Gay Fathers’ Perspectives on their 4-12-Year-Old Children’s Outdoor Risky Play Behaviour and ‘Good’ Fathering

2018· article· en· W2902108345 on OpenAlexaff
Michelle E. E. Bauer, Audrey R. Giles

Bibliographic record

VenueQualitative Research in Sport Exercise and Health · 2018
Typearticle
Languageen
FieldMedicine
TopicInjury Epidemiology and Prevention
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsSAFERPsychologyDevelopmental psychologyEXPOSESocial psychologyComputer security

Abstract

fetched live from OpenAlex

In this study, we address the question, ‘What are single, stay-at-home, and gay fathers’ perspectives of their 4– 12-year-old children’s outdoor risky play behaviours and how do they relate to discourses of good fathering?’ Through the use of semi-structured interviews, poststructural feminist theory, and critical discourse analysis, we identified five key discourses: Children’s play is safer now than when the participants were children; fathers need to know what each child needs for the child to be safe outdoors; fathers need to protect their children from danger; it’s good to expose children to outdoor risky play; experiencing scrapes and bruises is a part of growing up. The results both reaffirm and resist dominant discourses on good fathering. Further research on this topic is crucial, as fathers play an important role in their children’s experiences of outdoor risky play and injury.

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)0.006
metaresearch head score (Gemma)0.006
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0050.006
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.002
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 head0.182
GPT teacher head0.503
Teacher spread0.321 · 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

Citations13
Published2018
Admission routes1
Has abstractyes

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