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Record W4377139217 · doi:10.1080/10530789.2023.2205189

The challenges of comorbidities: a qualitative analysis of substance use disorders and offending behaviour within homelessness in the UK

2023· article· en· W4377139217 on OpenAlexfundno aff
Honor Sibthorp Protts, Steve Sharman, Amanda Roberts

Bibliographic record

VenueJournal of Social Distress and the Homeless · 2023
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
FundersGambling Research Exchange OntarioNational Institute for Health and Care ResearchSociety for the Study of Addiction
KeywordsPrisonFeelingSubstance useThematic analysisMainstreamPsychologyQualitative researchInclusion (mineral)Social exclusionEmpirical researchTherapeutic communityClinical psychologyPsychiatryCriminologySocial psychologySociologyPolitical science

Abstract

fetched live from OpenAlex

Homelessness and rough sleeping are currently on the rise in England. Literature evidences an empirical relationship between substance use disorders and offending behavior within homelessness. This qualitative study explores this relationship from the perspective of those currently experiencing homelessness and substance use disorders, with an offending history. Thematic analysis identified substance use disorders as the dominant factor in the continuous relationship between three. Furthermore, when discussing their experiences of prison, participants did not identify prison as a deterrent from committing offenses. Feelings of stigmatization and marginalization from mainstream society were also identified, but participants expressed feelings of social inclusion within their marginalized groups. These findings, and their implications for support services in the community, are discussed in this paper.

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)0.004
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 score0.304
Threshold uncertainty score0.915

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.088
GPT teacher head0.423
Teacher spread0.335 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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