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Record W2262482169

Housing for Assisted Living in Inner-City Winnipeg: A Social Analysis of Housing Options for People with Disabilities

2011· article· en· W2262482169 on OpenAlexfundaboutno aff
Michelle Owen, Colleen Watters

Bibliographic record

VenueWinnSpace (University of Winnipeg) · 2011
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Winnipeg
KeywordsAssisted livingAffordable housingHousing FirstPublic housingSociologyInner cityGerontologySocioeconomicsEconomic growthPsychologyEconomicsMedicinePsychiatry
DOInot available

Abstract

fetched live from OpenAlex

People with disabilities who have complex health and housing needs have limited housing options. Younger adults with disabilities, for example, are inappropriately placed in personal care homes with seniors when the cost of supporting a person in her or his own home exceeds the cost of supporting her or him in an institutional setting. Over the last decade, a working group called the Housing for Assisted Living (HAL) Committee has been seeking a solution to this problem in Winnipeg. The HAL Committee recently identified a building in the Logan area of Winnipeg's Inner City to re- develop as an assisted living facility that will provide a range of on-site support services for people with disabilities within an integrated setting.
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\nThis research project gathered information about social issues in the area where the assisted living facility is being developed. The findings will help ensure the long-term success of the HAL project, which will be beneficial for people with disabilities in particular and Winnipeg as a whole.
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\nWorking from a cross-disability perspective, we utilized a participatory action research approach. Thirty in-depth qualitative interviews were conducted with people with disabilities who have complex health and housing needs, people with disabilities currently living in the Inner City, and representatives of agencies that provide housing and other services in Winnipeg to people with disabilities. The data from these interviews was analyzed and the major themes were compiled into a preliminary report that was distributed to all study participants who reviewed the research findings and provided feedback.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.276
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.087
GPT teacher head0.337
Teacher spread0.250 · 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.

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

Citations5
Published2011
Admission routes2
Has abstractyes

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