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Uso de drogas ilícitas e perspectivas críticas de familiares e pessoas próximas, na cidade do Rio de Janeiro, Zona Norte, Brasil

2009· article· pt· W1599686494 on OpenAlexaffabout
Octavio Fernández‐Amador, Bruna Brands, Edward M. Adlaf, Norman Giesbrecht, Laura Simich, Maria da Glória Miotto Wright

Bibliographic record

VenueRevista Latino-Americana de Enfermagem · 2009
Typearticle
Languagept
FieldSocial Sciences
TopicYouth, Drugs, and Violence
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental HealthHealth Canada
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

This article presents the partial results of a multicenter, qualitative study, which involved seven Latin-American countries and Canada. The results presented refer to Northern Rio de Janeiro (city), Brazil. The objective of the study was to describe the perspective of relatives/acquaintances of illicit drug users about protective and risk factors, prevention initiatives, treatment services, and legal aspects regarding illicit drugs. Interviews were performed with 99 individuals, who reported being affected by their relationship with an illicit drug user (relative or acquaintance), approaching their perspectives regarding the key-domains. Most participants were women (73.7%); relatives who used drugs were mostly men (78.2%); the most consumed drug was marijuana (77.8%). The highlighted protective factor was having recreational-sports activities in the community (88.9%), and the risk factor was curiosity for trying something new (94.4%). The main treatment services were Church Groups (51.5%), and participants stated that laws should be more punitive (82.8%). In conclusion, this information is essential to fight against drug use/abuse, showing that there is a need for actions that consider different perspectives at different levels.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.264
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.002
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.347
Teacher spread0.312 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations7
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueRevista Latino-Americana de EnfermagemSame topicYouth, Drugs, and ViolenceFrench-language works237,207