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Record W2042688036 · doi:10.1081/ja-120023391

How Can Sociological Theory Help Our Understanding of Addictions?

2003· review· en· W2042688036 on OpenAlexaff
Manuella Adrian

Bibliographic record

VenueSubstance Use & Misuse · 2003
Typereview
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsAddictionSociological theoryCriminologySociologyContext (archaeology)Field (mathematics)PopulationPsychologyPerspective (graphical)Criminal justiceSocial psychologyPsychiatrySocial scienceDemography

Abstract

fetched live from OpenAlex

Those who work in the addiction field usually use the pharmacological or medical model, psychological theories of behavior, or operate within the confines of a criminal justice perspective. Contributions from the field of sociology are limited to use of the methods of sociological investigations, primarily population surveys, which, typically, are used to identify groups at-risk for specific types of drug use. Surveys have identified illicit drug use as, predominantly, a problem of young males, whereas prescription drug use is predominantly a problem of middle-aged and older women in industrialized countries. Experts in addiction have accused sociologists who study addiction of being "atheoretical." Paradoxically, in the sociology field, the most highly cited article is Merton's theory of addiction. This article will examine the contributions of sociological theory to our understanding of addiction, including social definitions of "the problem of addiction" and mechanisms to account for individual drug use within a social context that defines it as problematic.

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)0.006
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0070.005
Science and technology studies0.0020.017
Scholarly communication0.0050.015
Open science0.0020.002
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0030.001

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 head0.401
GPT teacher head0.437
Teacher spread0.036 · 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 designTheoretical or conceptual
Domainnot available
GenreReview

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

Citations37
Published2003
Admission routes1
Has abstractyes

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