Pathways to Pathological Gambling: Identifying Typologies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The majority of explanatory models of pathological gambling fail to differentiate specific typologies of gamblers despite recognition of the multi-factorial causal pathways to its development. All models inherently assume that gamblers are a homogenous population; therefore theoretically derived treatments can be effectively applied to all pathological gamblers. This article describes a comprehensive and alternative conceptual-pathway model that identifies three main subgroups: "normal," emotionally vulnerable and biologically based impulsive pathological gamblers. All three groups are exposed to common influences related to ecological factors, cognitive processes and contingencies of reinforcement. However, predisposing emotional stresses and affective disturbances for one group, and biological impulsivity for another, are additional risk factors of aetiological significance in identifying separate subtypes. The implications for treatment are discussed with particular reference to the need to match client subtype with specific treatment interventions.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it