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Record W4376113662 · doi:10.1080/14927713.2023.2211583

Disrupting, adapting and discovering family leisure during COVID-19

2023· article· en· W4376113662 on OpenAlexaffvenueabout
Charlene S. Shannon

Bibliographic record

VenueLeisure/Loisir · 2023
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Phenomenology (philosophy)Leisure activityFamily lifePsychologyFamily memberAdaptation (eye)2019-20 coronavirus outbreakSocial psychologySociologyMedicineSocioeconomicsDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

COVID-19 and the associated restrictions influenced family life including the practice of family leisure of those living in the same household and those who did not. The purpose of this study was to explore how individuals’ family leisure was affected by the COVID-19 restrictions in New Brunswick, Canada, and the ways individuals and their families adapted to those restrictions. Phenomenology guided the study. Interviews that utilized a photo elicitation technique were conducted virtually with 12 women, 3 men, and 1 gender fluid individual. The findings revealed the lockdown in March 2020 contributed to a ‘disruption to valued family leisure’. A period of ‘adaptation, exploration, and discovery’ followed characterized by determining what family leisure would include through participation in home-based, outdoor, and virtual family activities. Loosened restrictions and the opportunity to bubble with another household introduced the experience of ‘expanding family leisure’ as participants considered how family members would bubble.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.391
Threshold uncertainty score0.778

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.006
Scholarly communication0.0030.001
Open science0.0010.005
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 head0.047
GPT teacher head0.339
Teacher spread0.292 · 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 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

Citations4
Published2023
Admission routes3
Has abstractyes

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