Bibliographic record
Abstract
Uusitalo, S. (2015). Addiction, recovery and moral agency: Philosophical considerations. The International Journal Of Alcohol And Drug Research, X(Y), N-M. doi:http://dx.doi.org/10.7895/ijadr.vXiY.190 Aims: The purpose of this paper is to argue that it is important to recognize that addicts are morally accountable even for their addictive action, as moral agency is more generally an important factor in full-blown human agency. The challenge is to identify the problems that addicts have in their agency without discarding their potentially full-blown agency. Design: In philosophy of agency, moral responsibility and accountability, in particular, may refer to control over one’s action. I discuss this control as reason-responsiveness and, on a more general level, illustrate the importance of moral agency to human agency with a contrasting example of psychopaths and addicts as agents. Measures: A philosophical analysis is carried out in order to argue for the relevance and importance of moral accountability in therapeutic models of addiction. Findings: The example of psychopaths and addicts illustrates that moral agency is part of full-blown human agency, as psychopaths are generally believed to lack moral skills common to non-psychopathic individuals. I argue that addicts are not analogous to psychopaths in the framework of moral agency in this respect. Conclusions: By fleshing out the conceptual considerations in the framework of addiction therapies, I clarify the relevance and importance of moral accountability in therapeutic models of addiction. If evidence-based therapies attempt to restore the addict’s full-fledged agency at least in respect to addiction, then acknowledging addicts’ moral accountability for their action does matter.
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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 | 0.014 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.066 |
| Scholarly communication | 0.007 | 0.013 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.011 | 0.013 |
| Insufficient payload (model declined to judge) | 0.004 | 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".