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Record W1573215446 · doi:10.1177/070674370104600107

A Social Problem Index for Canada

2001· article· en· W1573215446 on OpenAlexaffvenueabout
An gus H Thomp son, Andrew Howard, Yan Jin

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2001
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsAlberta Health
Fundersnot available
KeywordsIndex (typography)HomicidePsychologySocial issuesDemographySocial psychologyPoison controlHuman factors and ergonomicsSociologyMedicineEnvironmental healthEconomicsEconomic growth

Abstract

fetched live from OpenAlex

OBJECTIVE: To construct an index that represents the general level of social problems among Canadian provinces and territories. METHOD: Factor weights were used to combine provincial and territorial rates for homicide, attempted murder, assault, sexual assault, robbery, divorce, suicide, and alcoholism into a single Social Problem Index. RESULTS: The resulting index demonstrated strong positive intercorrelations among its factors across provinces. That is, provinces that showed high rates on one factor tended to show high rates on the others as well. The validity of the Social Problem Index is demonstrated by its positive correlation with an independent measure of the likelihood of having experienced personal trauma. CONCLUSIONS: The robust nature and apparent validity of the Social Problem Index suggest that it can be well used for needs assessments and theoretical studies and as a feedback mechanism to national, provincial, and community leaders on the social problem status of their particular jurisdictions.

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)0.007
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: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.052
Threshold uncertainty score0.374

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0120.011
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0150.002

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 head0.058
GPT teacher head0.385
Teacher spread0.328 · 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

Citations8
Published2001
Admission routes3
Has abstractyes

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