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Record W2122107813 · doi:10.1177/104973200129118228

Narratives of Identity: Re-presentation of Self in People Who Are Homeless

2000· article· en· W2122107813 on OpenAlexaff
Katherine Boydell, Paula Goering, Tammy Lee Morrell-Bellai

Bibliographic record

VenueQualitative Health Research · 2000
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsCentre for Addiction and Mental HealthUniversity of Toronto
Fundersnot available
KeywordsIdentity (music)Presentation (obstetrics)NarrativeQualitative researchPersonal identityPsychologySocial psychologySocial identity theoryHierarchySociologySelf-conceptSocial groupMedicineSocial sciencePolitical scienceAesthetics

Abstract

fetched live from OpenAlex

The problem of homelessness is a pressing social and health concern ascribed to the interaction between personal, social, economic, and service system resources. The article is based on a qualitative study of the experiences of 29 homeless individuals. In-depth interviews were conducted with single adult shelter users. Analysis revealed the self to be a process that was continually developing. Participants tacitly locate their self-concepts in the past, present, and future. These time frames reflect the form and content of self. They also reveal hopes, dreams, beliefs, and understandings about self. The ways in which homelessness discredits notions of self and personal identity, and the hierarchy of identify with which homeless individuals use to cope are also examined.

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)0.010
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0100.016
Scholarly communication0.0070.009
Open science0.0010.011
Research integrity0.0020.004
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 head0.384
GPT teacher head0.650
Teacher spread0.266 · 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 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

Citations194
Published2000
Admission routes1
Has abstractyes

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