Submitted for the Canadian Centre on Substance Abuse (CCSA)
Bibliographic record
Abstract
This report provides an overview of the development, validation and reliability testing of the Canadian Problem Gambling Index, developed over the last three years. This research was conducted by a research team under the aegis of the Canadian Centre on Substance Abuse for the Inter-Provincial Task Force on Problem Gambling. The goal was to develop a new, more meaningful measure of problem gambling for use in general population surveys, one that included more indicators of the social and environmental context of gambling and problem gambling. The project was divided into two phases. Phase I was an examination of how problem gambling had been conceptualized, defined and measured in the literature, and the development or synthesis of a new conception, definition and means of measurement. This phase of the project involved an extensive review of the literature, and synthesis of the relevant literature into an integrated conceptual framework for our definition of problem gambling. The framework and the resulting definition were then put before a panel of experts in the field to ensure the new construct was adequately defined. After several rounds of consultation and feedback, a draft index based on the literature and feedback process was produced The second phase of this project was the fine tuning, validity and reliability testing of the index
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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.167 | 0.040 |
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".