Why, by Whom and How?
Bibliographic record
Abstract
To strengthen the right to support for people with gambling problems in Sweden, legislative changes were enacted in 2018. This study aims to critically examine how problems and solutions are represented in 69 appeals concerning gambling treatment within the general administrative court (2014–2022) and to assess how these representations have evolved following the legal amendments. The study employs Bacchi’s WPR approach to scrutinize court judgments. The results reveal that gambling problems are unequivocally recognized as severe issues requiring intervention, with both explicit and implicit notions of the problem rooted in the concept of loss of control. Prior to the legal amendments, rulings primarily focused on identifying the responsible actor for providing care, often framed within a medical discourse. Post-amendment, the focus shifted to how treatment needs should be met, emphasizing an evidence-based discourse. These varying representations produce discursive, subjectifying, and material consequences, significantly affecting access to different welfare interventions. The new legislation has solidified the responsibility of social services to provide treatment for gambling problems. However, as the study demonstrates, responsibilization of gamblers occurs not only in policy and treatment frameworks, but also within the court system.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.013 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".