The brain craving for gambling? Neurosciences and addiction concept in clinical practice
Bibliographic record
Abstract
Helén, I., & Toivio, J. (2015). The brain craving for gambling? Neurosciences and addiction concept in clinical practice. The International Journal Of Alcohol And Drug Research, 4(1), 45-51. doi:http://dx.doi.org/10.7895/ijadr.v4i1.202Aims: Paper discusses the impact of the neuroscientific concept of addiction and expectations related to neurosciences in a clinical setting for treatment of addiction disorders.Design: A case study based on qualitative analysis of scientific publications, research plans, presentations, and interviews of Finnish experts in gambling addictions.Setting: The case studied is a joint project for experimentation of medication (naltrexone) in treatment of gambling addiction by National Institute of Health and Welfare (THL) and Gambling Clinic, a center specialized in counseling for gambling addicts in Helsinki.Results: Although Finnish experts think that deep down all addictions share the same neural mechanisms, they consider gambling addiction a complex phenomenon. Clinical experiments seem to have two parallel objectives: neurophysiological malfunctions of the brain and the addict as the person. Two epistemologies and two concepts of addiction are working side by side in the clinical reasoning of the Finnish experts: the neurobiological one for framing the ‘addicted brain’, and the one derived from cognitive behavioral therapy for the addict.Conclusions: The role of the neurobiological concept of gambling addiction is to back up the therapeutic promise of the experimental project. In a reciprocal manner, the expectation to extend treatment options by the project findings justifies the neuroscientific approach.
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 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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.016 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| 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".