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Record W2000353945 · doi:10.1186/1478-4505-5-14

Housing, income support and mental health: Points of disconnection

2007· article· en· W2000353945 on OpenAlexaffabout
Cheryl Forchuk, Libbey Joplin, Ruth Schofield, Rick Csiernik, Carolyne Gorlick, Katy Turner

Bibliographic record

VenueHealth Research Policy and Systems · 2007
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsInnovation, Science and Economic Development CanadaMcMaster UniversityLawson Health Research InstituteWestern University
Fundersnot available
KeywordsDisconnectionSocial policyGovernment (linguistics)Mental healthHealth policyEconomic growthAffordable housingBusinessPolitical scienceEconomicsHealth careMedicine

Abstract

fetched live from OpenAlex

There exists a disconnection between evolving policies in the policy arenas of mental health, housing, and income support in Canada. One of the complexities associated with analysing the intersection of these policies is that federal, provincial, and municipal level policies are involved. Canada is one of the few developed countries without a national mental health policy and because of the federal policy reforms of the 1970s, the provincial governments now oversee the process of deinstitutionalization from the hospital to the community level. During this same period the availability of affordable housing has decreased as responsibility for social housing has been transfered from the federal government to the provincial and/or municipal levels of government. Canada also stands alone in terms of being a developed nation without national housing policy instead what is considered "affordable" housing is partially dependant upon individuals' personal economic resources. As well, over the past decade rates of income supports have also been reduced. Psychiatric survivors have long been identified as being at risk for homelessness, with the disconnection existing between housing, income and mental health policies and the lack of a national policy in any of these policies areas further contributing to this risk.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
models agreeAgreement compares identical category sets and study designs across arms.

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)0.017
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.206
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
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 head0.347
GPT teacher head0.599
Teacher spread0.252 · 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

Labeled directly by 2 models reading the full record.

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

Citations32
Published2007
Admission routes2
Has abstractyes

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