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Record W4297905413 · doi:10.3389/feduc.2022.957543

The impact of school attachment and parental involvement on the positive mental health of 2SLGBTQ + students during COVID-19

2022· article· en· W4297905413 on OpenAlexaffabout
Christopher Campbell, Ley Fraser, Tracey Peter

Bibliographic record

VenueFrontiers in Education · 2022
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMental healthGovernment (linguistics)Coronavirus disease 2019 (COVID-19)PandemicPsychologyPublic healthPolitical scienceMedicinePsychiatryNursing

Abstract

fetched live from OpenAlex

On March 11th, 2020, the World Health Organization (WHO) declared the worldwide outbreak of COVID-19 as a pandemic. On the following day, the Ontario government (Canada’s most populous province) ordered all public schools to close. By Monday, March 16th, 2020, all public schools (and most private schools) in Canada announced plans to physically shutter schools, with a shift to remote and online learning to follow soon after. This unprecedented shift in learning environment for young Canadians came at a time when the onset of the COVID-19 pandemic was creating a challenging environment for the mental health of all Canadians. While all students may have struggled to cope, 2SLGBTQ + students faced an unusually complex shift, as their school and home environments may have contributed differentially to the social supports and acceptance (related to their 2SLGBTQ + identity or identities) that their cisgender heterosexual peers routinely experience in their social surroundings. In this paper, we explore the relationship between school attachment, parental involvement and positive mental health in 2SLGBTQ + youth using data collected as part of the Second Annual School Climate Survey on Homophobia, Biphobia, and Transphobia in Canadian Schools.

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 score0.108
Threshold uncertainty score0.985

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.027
GPT teacher head0.437
Teacher spread0.410 · 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

Citations0
Published2022
Admission routes2
Has abstractyes

Explore more

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