MétaCan
Menu
Back to cohort
Record W2267030856

A Legal Framework for Supportive Housing for Seniors: Options for Canadian Policy Makers

2006· article· en· W2267030856 on OpenAlexaffabout
Margaret Hall

Bibliographic record

VenueSSRN Electronic Journal · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicElder Abuse and Neglect
Canadian institutionsThompson Rivers University
Fundersnot available
KeywordsSupportive housingHotlineLegislationExcellenceBusinessPublic relationsResource (disambiguation)Public administrationPolitical scienceMedicineNursingEngineeringLaw
DOInot available

Abstract

fetched live from OpenAlex

This report considers a range of approaches to the regulation of supportive housing for seniors. These approaches take into account the special hybrid quality of supportive housing as housing with services and the particular needs of seniors, especially at the high assisted living end of the supportive housing range. The methodology for the research included a review of literature and legislation in Canada, the United Kingdom, United States, and Australia; consultation with seniors and with professional stakeholders; an evaluation of potential approaches to regulation and possible options to supplement or support regulation (including a National Working Group on Supportive Housing to create best practices guidelines, a Supportive Housing Centre of Excellence, elder ombudsmen, and an information database and seniors' hotline). The Report is intended to serve as an information resource for Canadian policy makers and others concerned with supportive housing for seniors.

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)0.041
metaresearch head score (Gemma)0.053
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.120
Threshold uncertainty score0.872

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0410.053
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.006
Science and technology studies0.0280.019
Scholarly communication0.0240.011
Open science0.0080.009
Research integrity0.0190.011
Insufficient payload (model declined to judge)0.0080.001

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 head0.012
GPT teacher head0.318
Teacher spread0.305 · 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 designNot applicable
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
Published2006
Admission routes2
Has abstractyes

Explore more

Same venueSSRN Electronic JournalSame topicElder Abuse and NeglectFrench-language works237,207