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Record W1991844790 · doi:10.4172/2167-1168.1000115

A Systematic Review on the Intersection of Homelessness and Healthcare in Canada

2012· review· en· W1991844790 on OpenAlexaboutno aff
Vivian Darkwah

Bibliographic record

VenueJournal of Nursing & Care · 2012
Typereview
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsInclusion (mineral)Health careScope (computer science)NarrativeIntersection (aeronautics)NursingNarrative reviewQualitative researchOrder (exchange)PsychologyMedicineSociologyPolitical scienceBusinessGeographySocial scienceSocial psychology

Abstract

fetched live from OpenAlex

Background: Nurses must understand the needs and barriers of people who are homeless when they are in a health care environment in order to render effective care. Objective: The objective of this review is to synthesize research findings on studies that examine the needs and barriers of people who are homeless in Canada when they intersect with health care providers. Methods: A scope of manuscripts, published in English from 1980 to 2011 that assess the needs and barriers of people experiencing homelessness in Canada when in the health sector without limitation on study design from different electronic databases and manual searches, was conducted. Results: Six articles (N=4 qualitative, N=2 quantitative) met the inclusion and exclusion criteria. Eight themes emerged from a narrative synthesis of the findings. Conclusion: Individuals who are homeless have multiple needs when in the health care sector. Thus, collaboration among different disciplines is essential in order to provide them with holistic care.

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)0.010
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.508
Threshold uncertainty score0.979

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.035
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0170.029
Science and technology studies0.0030.002
Scholarly communication0.0040.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.126
GPT teacher head0.463
Teacher spread0.336 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations9
Published2012
Admission routes1
Has abstractyes

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