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Record W654035944 · doi:10.4135/9781483392240.n285

Mexican Mafia

2019· reference-entry· en· W654035944 on OpenAlexaboutno aff

Bibliographic record

VenueThe SAGE Encyclopedia of Criminal Psychology · 2019
Typereference-entry
Languageen
FieldSocial Sciences
TopicCrime, Illicit Activities, and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyComputer science

Abstract

fetched live from OpenAlex

It has been called the most dangerous gang in American history. In Los Angeles alone it is responsible for over 100 homicides per year. Although it has fewer than 300 members, it controls a 40,000-strong street army that is eager to advance its agenda. It waves the flag of the Black Hand and its business is murder. Although known on the streets for over fifty years, the Mexican Mafia has flown under the radar of public awareness and has flourished beneath a deep cover of secrecy. Members are forbidden even to acknowledge its existence. For the first time in its history, the Mexican Mafia is now getting the attention it has been striving to avoid. In this briskly written and thoroughly researched book, Tony Rafael looks at the birth and the blood-soaked growth of this criminal enterprise through the eyes of the victims, the dropouts, the cops and DAs on the front lines of the war against the Mexican Mafia. The first book ever published on the subject, Southern Soldiers is a pioneering work that unveils the operations of this California prison gang and describes how it grew from a small clique of inmates into a transnational criminal organization. As the first prison gang ever to project its power beyond prison walls, the Mexican Mafia controls virtually every Hispanic neighborhood in Southern California and is rapidly expanding its influence into the entire Southwest, across the East Coast, and even into Canada. Riding a wave of unchecked immigration and seemingly beyond the reach of law enforcement, the Mexican Mafia is poised to become the Cosa Nostra of twenty-first-century America.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.421
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.041
GPT teacher head0.358
Teacher spread0.317 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations16
Published2019
Admission routes1
Has abstractyes

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