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Record W2113613900 · doi:10.1093/hsw/33.4.259

The Impact of Kin and Fictive Kin Relationships on the Mental Health of Black Adult Children of Alcoholics

2008· article· en· W2113613900 on OpenAlexfundno aff
J. Camille Hall

Bibliographic record

VenueHealth & Social Work · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicChild Welfare and Adoption
Canadian institutionsnot available
FundersAtlantic Canada Opportunities Agency
KeywordsPsychologyMental healthDevelopmental psychologyKinshipContext (archaeology)Coping (psychology)Qualitative researchClinical psychologySocial psychologyPsychotherapistSociology

Abstract

fetched live from OpenAlex

The purpose of this qualitative study was to examine how kin and fictive kinship relationships help to ameliorate or buffer responses to parental alcoholism and the breakdown in parenting. This qualitative study investigated coping responses developed by college students, who self-identified as adult children of alcoholics (ACOAs) who lived with an alcoholic parent or caregiver. In-depth interviews and follow-up participant checks were used. A descriptive model was developed describing conditions that affected the development of positive self-esteem, the phenomena that arose from those conditions, the context that influenced strategy development, the intervening conditions that influenced strategy development, and the consequences of those strategies. Subcategories of each component of the descriptive model are identified and illustrated by narrative data in relation to the ACOAs' psychological well-being. Implications for research, 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 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)0.002
metaresearch head score (Gemma)0.005
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 score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0050.004
Scholarly communication0.0010.001
Open science0.0010.003
Research integrity0.0010.001
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 head0.047
GPT teacher head0.351
Teacher spread0.305 · 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

Citations27
Published2008
Admission routes1
Has abstractyes

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