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Record W4386325076 · doi:10.5206/ijoh.2023.3.15051

Community Stakeholders’ Perceptions of the Impact of the Coronavirus Pandemic on Homelessness in Canada

2023· article· en· W4386325076 on OpenAlexaffvenueabout
Cheryl Forchuk, Sara Husni, Leanne Scott, Jonathan Serrato, Richard Booth

Bibliographic record

VenueInternational Journal on Homelessness · 2023
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsParkwood InstituteLawson Health Research InstituteWestern University
Fundersnot available
KeywordsThematic analysisPandemicQualitative researchFocus groupPerceptionMental healthPublic healthSupportive housingEthnographyMental illnessSociologyPsychologyEconomic growthPolitical scienceCoronavirus disease 2019 (COVID-19)GerontologyMedicineNursingDiseasePsychiatrySocial science

Abstract

fetched live from OpenAlex

Homelessness was already a well-known risk factor contributing to premature death, morbidity, mental illness, and substance use disorder. The coronavirus disease for 2019 (COVID-19) pandemic has amplified disparities in Canada’s public health system, disproportionately impacting people experiencing homelessness. The present study aimed to investigate the impact of the COVID-19 pandemic on the homelessness situation in Canada from community stakeholders’ perceptions. The study used qualitative research approaches underlain by focused ethnography tenets. The sample includes 200 service providers from 28 communities across Canada (at least one site in each province and territory) to participate in virtual focus groups. Data analysis followed a four-step ethnographic approach for thematic analysis in qualitative research. Six main themes emerged: (a) system changes precipitated by the COVID-19 pandemic; (b) personal changes in life circumstances; (c) previous strategies no longer working; (e) opportunities; (d) some things getting better; (f) an overall increase in first time and recurrent homelessness in Canada. The study findings underscored mechanisms required to help ‘tip the scale’ in affording people experiencing homelessness the opportunity to avoid or exit homelessness.

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 categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.223
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.002
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 head0.164
GPT teacher head0.441
Teacher spread0.277 · 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.

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

Citations2
Published2023
Admission routes3
Has abstractyes

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