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Record W4319839628 · doi:10.1177/21568693221141927

Drinker Identity Development: Shame, Pride, and a Thirst to Belong

2023· article· en· W4319839628 on OpenAlexaff
Colter J. Uscola

Bibliographic record

VenueSociety and Mental Health · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Cultural Dynamics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBelongingnessPrideSocial psychologyIdentity (music)PsychologyShameIntervention (counseling)Construct (python library)Identity formationSocial identity theoryPsychology of selfSociologySelf-conceptSocial groupPolitical science

Abstract

fetched live from OpenAlex

Identity theorists assume that individuals intentionally construct and maintain a culturally valued sense of self. Although this logic makes sense for positive identities—doctor, parent, or scientist—it becomes questionable when applied to the construction of negative, or stigmatized, identities, such as that of a drinker. By interviewing 16 members of a metropolitan recovery community, I focus on how marginalized identities form seemingly absent of intention. In doing so, I show how stress and negative messaging from guardians, peers, and community members produce persistent painful emotions that restrict access to culturally valued identity pathways and steer individuals toward spaces of consumption. Through each lost socially valued role, the drinker identity becomes more salient, achieving more importance in daily life and becoming central to individuals’ lived experiences. That is, the drinker role becomes a primary source of positive affect and belongingness when these essential ingredients of social life are unobtainable elsewhere. More broadly, I challenge current theoretical assumptions that dominated intervention strategies and recovery policy for decades and offer considerations for policy and intervention programs.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.520
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.026
GPT teacher head0.350
Teacher spread0.324 · 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.

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

Citations4
Published2023
Admission routes1
Has abstractyes

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