MétaCan
Menu
Back to cohort
Record W2964323075 · doi:10.1177/1049732319862532

Fixed Nodes of Transience: Narratives of Homelessness and Emergency Department Use

2019· article· en· W2964323075 on OpenAlexafffund
Ross McCallum, Maria I. Medved, Diane Hiebert‐Murphy, Jino Distasio, Jitender Sareen, Dan Chateau

Bibliographic record

VenueQualitative Health Research · 2019
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of WinnipegUniversity of Manitoba
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsNarrativeEmergency departmentAgency (philosophy)Context (archaeology)Narrative inquiryHealth careSociologyPopulationPsychologyQualitative researchMedicineNursingGender studiesPolitical scienceHistorySocial science

Abstract

fetched live from OpenAlex

Discourse in popular media, public policy, and academic literature contends that people who are homeless frequently make inappropriate use of hospital emergency department (ED) services. Although researchers have investigated the ED experiences of people who are homeless, no previous studies have examined how this population understands the role of the ED in their health care and in their day-to-day lives. In the present study, 16 individuals participated in semistructured interviews regarding their ED experiences, and narrative analysis was applied to their responses. Within the context of narratives of disempowerment and discrimination, participants viewed the ED in differing ways, but they generally interpreted it as a public, accessible space where they could exert agency. ED narratives were also paradoxical, depicting it as a fixed place for transient care, or a place where they were isolated yet felt a sense of belonging. Implications for policy and practice are discussed.

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)0.008
metaresearch head score (Gemma)0.001
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 score0.021
Threshold uncertainty score0.706

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
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 science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.442
GPT teacher head0.629
Teacher spread0.188 · 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

Citations20
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueQualitative Health ResearchSame topicHomelessness and Social IssuesFrench-language works237,207