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Record W4285007422 · doi:10.1177/21568693221108766

Parent and/or Grandparent Attendance at Residential School and Dimensions of Cultural Identity and Engagement: Associations with Mental Health and Substance Use among First Nations Adults Living off Reserve

2022· article· en· W4285007422 on OpenAlexafffundabout
Tara Hahmann, Amanda Perri, Huda Masoud, Amy Bombay

Bibliographic record

VenueSociety and Mental Health · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsDalhousie UniversityThunderbird Partnership FoundationStatistics Canada
FundersCanadian Institutes of Health Research
KeywordsGrandparentAttendancePsychologyMental healthPopulationMoodAffect (linguistics)OddsPsychological interventionClinical psychologyAnxietyPsychiatryGerontologyDevelopmental psychologyMedicineEnvironmental healthLogistic regression

Abstract

fetched live from OpenAlex

Limited studies have assessed how parent and/or grandparent attendance at residential schools is associated with mental health and substance use among First Nations peoples living off reserve, while also considering how cultural dimensions relate to these outcomes. Analyses of the 2017 Aboriginal Peoples Survey revealed that the odds of self-reported diagnosed mood and anxiety disorders, past-year heavy drinking, and frequent marijuana use were significantly higher among First Nations adults living off reserve who had either a parent and/or grandparent who attended residential schools, even when controlling for covariates. In predicting diagnosed mood disorder, positive cultural identity affect and cultural engagement moderated the effect of parent residential school attendance while cultural exploration moderated the effect of two generations of attendance. Cultural exploration was a protective factor for grandparent residential school attendance in relation to past-year frequent marijuana use. Interventions that are trauma-informed and culturally-based should be considered for this population.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.802
Threshold uncertainty score0.973

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 studies0.0280.001
Scholarly communication0.0000.001
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 head0.031
GPT teacher head0.325
Teacher spread0.295 · 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.

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

Citations12
Published2022
Admission routes3
Has abstractyes

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