Réflexion psychodynamique : À propos d’une structure de personnalité toxicomaniaque spécifique à l’alcool et aux drogues dures
Bibliographic record
Abstract
The overconsumption of psychotropic substances is a major problem for contemporary societies. In the USA, 14.1% of the population between the age 15 and 54 have experienced addiction problems to alcohol during their lives while as 7.5% are addicted for life to other drugs (cannabis, cocaine, stimulants, etc). Many studies report that excessive consumption of alcohol, with or without illegal drug use, is associated to social conditions favoring the development of psychological distress and isolation. Although there are many studies on the differences between personality traits of alcoholics and drug users, few authors have examined the possibility to bring to the fore a specificity between the personality structures of the alcoholic and the drug user from a psychodynamic approach. This exploratory review of literature, first presents studies already conducted in order to identify common or distinct personality features for these types of addition. This article then reviews psychodynamic writings examining the possibility of a structural organization that is specific to addiction. Finally, the authors propose a few thoughts allowing to postulate on the existence of a structural organization specific to these two types of addiction.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".