Accurate yet problematic: the divided sentiments regarding brain-based addiction by professionals in the Finnish service system
Bibliographic record
Abstract
Background There is an ongoing debate regarding the value and applicability of brain-based understandings of addiction. This study examines how professionals in the Finnish addiction service system view this matter.Methods The study participants (n = 997) were recruited at different levels of policy-making, treatment, prevention work, education, administration and research. We created an online questionnaire containing both multiple-choice and open-ended questions. Quantitative and qualitative analyses were performed.Results There was a broad agreement among survey participants regarding the relevance and importance of brain-based understandings, per se. The support seemed to have increased a great deal in the past decades. On a closer view, a dichotomous attitude prevailed among the respondents: They expressed robust support for etiologies and ontologies of brain-based addiction, but simultaneously acknowledged some greater risks with neurocentrism and with wider implementations of neuroscientifically based interventions. New divisions of responsibility and the weakening of rights among concerned parties were presented as risk scenarios. The respondents feared that a medicalization of addiction would sideline social approaches.Conclusion The Finnish addiction service professionals were not prepared to let brain-based ideas of addiction guide the country’s addiction services but saw them as a useful supplementary hermeneutic and pedagogic tool.
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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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".