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Record W2052759542 · doi:10.1177/0044118x00032002005

Drifting Toward Mental Health

2000· article· en· W2052759542 on OpenAlexaff
Michael Ungar, Eli Teram

Bibliographic record

VenueYouth & Society · 2000
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsWilfrid Laurier UniversityMemorial University of Newfoundland
Fundersnot available
KeywordsMental healthEmpowermentPsychologyPsychological resilienceOpposition (politics)Social psychologyConstruct (python library)NarrativePower (physics)Coping (psychology)SociologyPsychotherapistPolitical sciencePolitics

Abstract

fetched live from OpenAlex

Interviews with 41 high-risk adolescents explained the link between the process of empowerment and mental health. Participants in this study demonstrated how aspects of power that enhance the construction of health-promoting identities form a base for personal and social resilience in youth. Without knowledge of postmodern theory, participants articulated the interdependence between their well-being and their capacity to influence the social discourses that construct their identities. As participants “drift” between these discourses, they seek the power to control the mental health resources required to maintain the identities that enhance their sense of well-being. Helping professionals can play an important role in this empowerment process by assisting high-risk youth redefine their personal narratives as health-seeking, in opposition to the stigmatizing stories others tell about them.

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)0.007
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.007
Scholarly communication0.0030.003
Open science0.0010.006
Research integrity0.0010.003
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 head0.112
GPT teacher head0.429
Teacher spread0.318 · 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 designObservational
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

Citations53
Published2000
Admission routes1
Has abstractyes

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