Bibliographic record
Abstract
The IMO has called for an end to the indifference to the damage being done by the scourge of alcohol, drugs and gambling addictions, proposing some wide-ranging proposals across a number of areas, writes Lloyd Mudiwa. While most news reports headlined with the IMO’s call for an immediate ban on sports sponsorship by the alcohol industry, the IMO’s Position Paper on Addiction and Dependency is wide-ranging in approach to the problem of addictions and recommends a number of measures against all the main problems, including drugs and gambling. Launching the paper, IMO President Dr Ray Walley told journalists that since the 1960s, the consumption of illegal drugs and alcohol had increased to a point where more than one-quarter of all Irish adults now state they had used an illegal psychoactive substance recreationally and more than half of all Irish adults were classified by the WHO criteria as harmful drinkers. In recent years, gambling addiction had received greater attention, as the ubiquity of internet access provided problem gamblers with an ever-present means of exacerbating their disorder, he added....
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.009 | 0.019 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".