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The Impact of COVID-19 Isolation Practices on Service Delivery to Persons Experiencing Homelessness and Concurrent Disorders

2022· article· en· W4313644543 on OpenAlexaffabout
M Young, Van Tuyl R

Bibliographic record

VenueAustin Anthropology · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsRoyal Roads University
Fundersnot available
KeywordsIsolation (microbiology)Coronavirus disease 2019 (COVID-19)Service delivery frameworkService providerSocial isolationService (business)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)NursingMedicinePublic relationsPsychologyBusinessPolitical scienceMarketingPsychiatryVirology

Abstract

fetched live from OpenAlex

This research examines the effect of COVID-19 isolation protocols on service provision to persons experiencing homelessness and concurrent disorders (PEHCD) in the province of British Columbia, Canada. Using mixed methods, 119 service providers completed a survey about experiences with COVID-19 isolation protocols. Of those, 25 participated in semi-structured interviews. In addition to documenting the challenges experienced by service providers, the results illustrate the creative and effective ways that service provision to PEHCD was maintained in the face of restrictions. This research builds on a pilot project conducted in Victoria, Canada in 2021, examining early impacts of COVID-19 isolation protocols on service delivery to PEHCD. This study extends the research to urban, rural, and remote communities across British Columbia.

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)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.725
Threshold uncertainty score0.553

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.006
Scholarly communication0.0030.001
Open science0.0020.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.093
GPT teacher head0.501
Teacher spread0.408 · 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 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

Citations1
Published2022
Admission routes2
Has abstractyes

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