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Record W4386909777 · doi:10.1080/07370016.2023.2256307

Exploring Frontline Shelter Staff Perspectives on the Healthcare Needs of Clients Experiencing Homelessness

2023· article· en· W4386909777 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Community Health Nursing · 2023
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsMcGill University
Fundersnot available
KeywordsThematic analysisHealth careNonprobability samplingNursingQualitative researchVisionService (business)Work (physics)MedicinePsychologyPublic relationsSociologyPolitical scienceBusinessEnvironmental healthPopulation

Abstract

fetched live from OpenAlex

PURPOSE: To examine healthcare service development needs for persons experiencing homelessness from the perspective of frontline staff at a homeless shelter in Montreal, Quebec. DESIGN: Qualitative descriptive design. METHODS: = 8), and thematic analysis. FINDINGS: Themes included: 1) Challenges meeting healthcare service needs in a shelter environment. 2) Visions for improving healthcare services while accounting for health issues and barriers to care. 3) Participants' own knowledge gaps around health and healthcare services. CONCLUSIONS: Future research should emphasize this group's crucial role in homelessness healthcare services development.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
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 head0.281
GPT teacher head0.479
Teacher spread0.198 · 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