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Aspectos legales del uso de drogas ilícitas en México

2009· article· es· W2011309603 on OpenAlex
Ruth Magdalena Gallegos Torres, Bruna Brands, Edward M. Adlaf, Norman Giesbrecht, Laura Simich, Maria da Glória Miotto Wright

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRevista Latino-Americana de Enfermagem · 2009
Typearticle
Languagees
FieldSocial Sciences
TopicSocial Issues and Policies in Latin America
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHumanitiesPhilosophyPsychology

Abstract

fetched live from OpenAlex

The objective of this cross-sectional, descriptive study was to obtain the opinions of a group of people about legal issues regarding addiction. Data collection was performed using a structured questionnaire with four themes. In order to participate, the individual could not use any drugs but should have a close relationship with a drug user. The data was processed using SPSS V. 14. There were 100 participants, 75% of whom were women, and 38% had a drug user as a friend, mainly cocaine and marijuana users. The participants had one opinion in common: laws should be more severe for people who use, sell, or transport drugs. The current laws do not improve consumers' criminal behavior. There is a need for further studies addressing people's opinion about this phenomenon in order to obtain a more realistic view of this drug issue.

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.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.843
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0010.002
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.022
GPT teacher head0.367
Teacher spread0.345 · 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