MétaCan
Menu
← Back to cohort
Record W4244314236 · doi:10.24124/2010/bpgub687

What's the link: An exploration of recovery and social support for individuals living with a mental illness.

2010· dissertation· en· W4244314236 on OpenAlexafffund
Erica R. Moore

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsCanadian HeritageUniversity of Northern British Columbia
FundersCanadian Mental Health Association
KeywordsMental illnessMental healthThematic analysisSocial connectednessSocial supportPsychologyQualitative researchQualitative propertyScale (ratio)Clinical psychologyApplied psychologySocial psychologyPsychiatrySociology

Abstract

fetched live from OpenAlex

Recovery from mental illness is a personal journey of transformation and has been found to be a deeply social process ...The intent of this research was to explore the relationship between an individual's recovery journey and social support for people living with a serious and persistent mental illness. Through the use of the Recovery Assessment Scale ...and Medical Outcomes Study: Social Support Survey Instrument ..., 35 participants provided quantitative data (phase one). From the quantitative data, a qualitative interview guide was fine-tuned, which was used for 10 one-on-one interviews (phase two). Demographic information was also gathered on participants from both phases. The qualitative data was analyzed using a thematic analysis, and the following five themes emerged: Work/volunteer opportunities Mental Health Services Peers Connectedness and Stigma. Through conducting this research, it is believed that a better understanding of the connection and relationship between the recovery process and social support was achieved which could begin to inform policy, practice, and future research in community mental health. As well, the beginnings of a definition of social support, from the perspectives of individuals living with a serious and persistent mental illness, was developed and may be helpful to address the present gap in the literature. --P. ii.

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)0.005
metaresearch head score (Gemma)0.006
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 score0.009
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0090.008
Scholarly communication0.0050.009
Open science0.0010.006
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 head0.186
GPT teacher head0.440
Teacher spread0.254 · 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

Citations0
Published2010
Admission routes2
Has abstractyes

Explore more

Same topicMental Health and Patient Involvement→French-language works237,207→