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Record W4391746475 · doi:10.1111/capa.12552

Unhoused women in Niagara: Lived expertise of homelessness in community‐engaged research

2024· article· en· W4391746475 on OpenAlexafffund
Joanne Heritz

Bibliographic record

VenueCanadian Public Administration · 2024
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsBrock University
FundersSocial Sciences and Humanities Research Council of CanadaBrock University
KeywordsDisadvantageLived experienceActive listeningCommunity engagementSociologyRace (biology)IntersectionalityGender studiesPublic relationsPolitical sciencePsychologyLaw

Abstract

fetched live from OpenAlex

Abstract How do we apply a gender lens to the housing needs of vulnerable women? The YWCA Niagara Region (YWCA) asked this question. Brock University's Niagara Community Observatory (NCO) partnered with the YWCA to identify the barriers to accessing safe and affordable housing in Niagara, with priority placed on community engagement and inclusive access to housing. The article has a two‐fold purpose. First, it provides an overview of community‐engaged research, focusing on the key principles and practices involved in listening to stories of women with lived expertise of homelessness facing discrimination or disadvantage compounded by intersectional identities of Indigeneity, race, gender and ability. Second, it reports on the making of a policy brief and video clip designed as advocacy tools for increasing awareness of the need for increased equitable access to safe and affordable housing for women and gender diverse peoples in Niagara.

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)0.006
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.548
Threshold uncertainty score0.898

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0330.028
Scholarly communication0.0100.005
Open science0.0020.012
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0050.000

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 head0.201
GPT teacher head0.461
Teacher spread0.260 · 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 designQualitative
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

Citations1
Published2024
Admission routes2
Has abstractyes

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