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Record W4297109376 · doi:10.1080/10875549.2022.2128977

Public Housing Tenants’ Strengths and Skills and Available Opportunities in Their Residential Environment to Put Them in Action

2022· article· en· W4297109376 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Poverty · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicKorean Urban and Social Studies
Canadian institutionsUniversité LavalUniversité du Québec à Montréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsAction (physics)Public housingBusinessEconomic growthSociologyEconomics

Abstract

fetched live from OpenAlex

This paper aims to empirically explore the strengths and skills among public housing tenants as well as the opportunities offered by their environment to use them. In Québec (Canada), 310 participants took part in interviews including open and closed-ended questions about their strengths and skills. Public housing tenants indicated possessing a diversity of strengths and skills. Although participants hinted toward a positive influence of their environment, they quantitatively evaluated the available opportunities to use their strengths and skills as moderately satisfying. The findings suggest a need for interventions specifically tailored to low-income populations such as public housing tenants.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.072
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.055
GPT teacher head0.236
Teacher spread0.181 · 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