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Record W3112258458 · doi:10.3167/ghs.2020.130305

Girls and Young Women Negotiate Wellbeing during COVID-19 in Quebec

2020· article· en· W3112258458 on OpenAlexaffabout
Jennifer Thompson, Sarah Fraser, Rocio Macabena Perez, Charlotte Paquette, Katherine L. Frohlich

Bibliographic record

VenueGirlhood Studies · 2020
Typearticle
Languageen
FieldHealth Professions
TopicHealth, psychology, and well-being
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsNegotiationPandemicCoronavirus disease 2019 (COVID-19)Gender studiesIndigenousYoung adultPolitics2019-20 coronavirus outbreakPsychologySociologyDevelopmental psychologyPolitical scienceMedicineSocial science

Abstract

fetched live from OpenAlex

In this article, we feature photographs and cellphilms produced by 13 girls and young women (aged 13 to 19) from urban, rural, and Indigenous areas of Quebec, Canada during the COVID-19 pandemic. Framed within girls’ studies, we present girls’ and young women’s creations and co-analysis about wellbeing during a period of lockdown. We explore how girls and young women restructured their routines at home as well as negotiated motivation and the pressure to be productive. We note that girls had more time than usual for creative activities and self-discovery and that they engaged with the politics of the pandemic and advocated for collective forms of wellbeing. Importantly, girls reported that participating in this research improved their wellbeing during this lockdown.

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)0.001
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 score0.082
Threshold uncertainty score0.189

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0260.006
Scholarly communication0.0040.001
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0070.000

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 head0.088
GPT teacher head0.443
Teacher spread0.354 · 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
Published2020
Admission routes2
Has abstractyes

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