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Record W4214649102 · doi:10.1071/py21188

Improving access for the vulnerable: a mixed-methods feasibility study of a pop-up model of care in south-eastern Melbourne, Australia

2022· article· en· W4214649102 on OpenAlexaff

Bibliographic record

VenueAustralian Journal of Primary Health · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of Calgary
FundersDepartment of Health, State Government of VictoriaU.S. Department of Health and Human Services
KeywordsPopulation healthService providerCommunity healthNegotiationService delivery frameworkMental healthHealth careGovernment (linguistics)Service (business)

Abstract

fetched live from OpenAlex

Access to appropriate health and social care is challenging for vulnerable populations. We used a 'pop-up' delivery model to bring community-based services in contact with communities with poor access to health and social care. Our aim was to examine whether pop-up events improve access to essential health and social support services for selected vulnerable communities and increase collaboration between community-based health and social services. Set in south-eastern Melbourne, two pop-up events were held, one with people at risk of homelessness attending a community lunch and the other with South Sudanese women helping at-risk youth. Providers represented 20 dental, housing, justice, employment and mental health services. We made structured observations of each event and held semi-structured interviews with consumers and providers. Pre-post surveys of managers assessed acceptability and perceived impact. We reached 100 community participants who had multiple needs, particularly for dentistry. Following the events, participants reported increased knowledge of services and access pathways, community members spoke of increased trust and partnerships between service providers were fostered. The pop-up model can increase provider collaboration and provide new options for vulnerable populations to access needed services. 'Bringing the service to the person' is a compelling alternative to asking consumers to negotiate complex access pathways.

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)0.012
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.366
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.214
GPT teacher head0.524
Teacher spread0.310 · 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.

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

Citations2
Published2022
Admission routes1
Has abstractyes

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