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Record W2470675953 · doi:10.1080/00981389.2016.1183553

The experiences of emergency department use by street-involved youth: Perspectives of health care and community service providers

2016· article· en· W2470675953 on OpenAlexafffund
David Nicholas, Amanda S. Newton, Christopher Kilmer, Avery Calhoun, Margaret A. deJong-Berg, Kathryn Dong, Faye Hamilton, Anne-Marie McLaughlin, Janki Shankar, Peter Smyth

Bibliographic record

VenueSocial Work in Health Care · 2016
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsMacEwan UniversityGovernment of AlbertaUniversity of AlbertaUniversity of Calgary
FundersCanadian Institutes of Health ResearchAlberta Centre for Child, Family and Community Research
KeywordsEmergency departmentAgency (philosophy)Service providerFocus groupNursingGrounded theoryHealth careService (business)MedicinePsychologyQualitative researchPublic relationsBusinessSociologyPolitical science

Abstract

fetched live from OpenAlex

Street-involved (SI) youth represent a significant proportion of urban homeless populations. While previous research has identified SI youth as substantial users of emergency department (ED) services and has examined their experiences of ED care, little is known about the experiences and perceptions of the service providers who assist these youth with health care related issues. Using grounded theory, individual interviews and focus groups were conducted with 20 community agency staff serving SI youth, 17 health service providers, two hospital administrators, and two hospital security personnel regarding their experiences in providing or facilitating ED care for SI youth. Results identify differences in expectations between SI youth and hospital staff, along with service issues and gaps, including relational barriers and resource constraints. Implications for practice and policy development are offered.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.244
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.079
GPT teacher head0.416
Teacher spread0.337 · 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 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

Citations4
Published2016
Admission routes2
Has abstractyes

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