Bibliographic record
Abstract
The Mafia began on a small island in the Mediterranean, Sicily. It grew to become a major political force in Italy, while its tentacles penetrated every aspect of life in the United States. Through drugs, it spread its influence to Britain, Canada and Australia. And through the gangster movies of Hollywood, including The Godfather and Goodfellas, it permeates popular culture. The History of the Mafia is full of blood-chilling characters, from Al Capone, who ran Chicago during Prohibition, and hitmen Louis Lekpe and Alberto Anastasia who founded Murder, Inc, to Totò Riina, 'boss of bosses', John Gotti, 'the Teflon don', and Bernardo 'The Tractor' Provenzano, who hid out from the law in a farmhouse for 43 years ... These were extraordinary men who lived through extraordinary times. The History of the Mafia tells the story of their lives, their families, their codes, their crimes and their cold-blooded murders. A long and enthralling tale, drenched in blood and scored with betrayal
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.041 | 0.007 |
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".