Bibliographic record
Abstract
As very few first person narratives have been written about women’s experience of problem gambling, Gripped by Gambling by Marilyn Lancelot is like a flower blooming in a desert. The opening words, “Please, not in front of my grandson”, spoken to the police as they are about to handcuff her, capture the anguish and pain that Marilyn’s few short years of gambling have created in her life. With candor and clarity Marilyn takes her readers through years of struggling with multiple addictions, putting each to bed only to have another pop up like a weasel in a midway game. The book unravels a childhood history of family alcoholism and abuse, her empty marriage, alcoholism, life as a single mother, the tragic loss of her second husband, and a series of relationships over the years. The book takes us with her into a two-year prison sentence, at the age of 60, for embezzling $300,000 from her employer.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.019 | 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".