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Record W3158768026 · doi:10.1080/01490400.2021.1920521

“I’ve Seen What Evil Men Do”: Military Mothering and Children’s Outdoor Risky Play

2021· article· en· W3158768026 on OpenAlexafffundabout
Michelle E. E. Bauer, Audrey R. Giles, Mariana Brussoni

Bibliographic record

VenueLeisure Sciences · 2021
Typearticle
Languageen
FieldPsychology
TopicAdventure Sports and Sensation Seeking
Canadian institutionsBC Children's HospitalUniversity of British ColumbiaUniversity of Ottawa
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsThematic analysisReflexivityContext (archaeology)PsychologySuicide preventionInjury preventionHuman factors and ergonomicsOccupational safety and healthPoison controlSocial psychologyEnvironmental healthSociologyQualitative researchPolitical scienceMedicineHistorySocial science

Abstract

fetched live from OpenAlex

The restrictions on children's outdoor risky play is emerging as a pressing public health concern. To the best of our knowledge, no research has examined military mothers' perspectives on outdoor risky play. Military mothers have unique knowledge of war and combat and potential threats to children's safety due to their communications with their partners in combat arms occupations. Their perspectives on outdoor risky play are important to consider to expand scholarly understandings of risk discourses in the context of military culture. We conducted semi-structured interviews with 16 military mothers from across Canada. The results of our reflexive thematic analysis are threefold: (1) Outdoor risky play in close physical proximity to strangers and cars is dangerous for children; (2) outdoor risky play should not result in children experiencing serious injuries; and (3) outdoor risky play can teach children to assess and manage risks.

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 score0.156
Threshold uncertainty score0.897

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.298
Teacher spread0.279 · 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

Citations1
Published2021
Admission routes3
Has abstractyes

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