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Record W2084621661 · doi:10.1300/j029v10n03_01

Inhalant Use by Canadian Aboriginal Youth

2001· article· en· W2084621661 on OpenAlexaboutno aff
Heather J. Coleman, Grant Charles, Jennifer Collins

Bibliographic record

VenueJournal of Child & Adolescent Substance Abuse · 2001
Typearticle
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsnot available
Fundersnot available
KeywordsIntoxicative inhalantPovertySubstance abuseIndigenousLogistic regressionPsychiatryGovernment (linguistics)MedicineAlcohol abusePsychologyEnvironmental healthPolitical science

Abstract

fetched live from OpenAlex

While inhalant abuse is a significant problem among Canada’s Aboriginal (indigenous) people, it is poorly understood. This study was conducted in response to these issues. The authors followed 78 Aboriginal young people who received treatment for inhalant abuse in a program established by the federal government. Data were based on a secondary analysis of case files as well as follow-up information from community workers.\nSeventy-four percent of the 78 young people tracked during follow- up relapsed after discharge from treatment. Many of the young people came from backgrounds marked by isolation, poverty, family violence and substance abuse. The average age these young people started using solvents was 9.72 years. Gasoline was the most common inhalant used. Inhalant use was often accompanied by alcohol and drug abuse. A logistic regression model predicting who would relapse indicated that young people who abused inhalants immediately before admission, those who were described as unmotivated in treatment and those who were hospitalized during treatment had the greatest risk of relapsing during follow-up. Implications are discussed.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.375
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.239
Teacher spread0.229 · 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

Citations38
Published2001
Admission routes1
Has abstractyes

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