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El consumo de drogas y su tratamiento desde la perspectiva de familiares y amigos de consumidores: Guatemala

2009· article· es· W2011952543 on OpenAlexaff
Jorge Bolívar Díaz C, Bruna Brands, Edward M. Adlaf, Norman Giesbrecht, Laura Simich, Maria da Glória Miotto Wright

Bibliographic record

VenueRevista Latino-Americana de Enfermagem · 2009
Typearticle
Languagees
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHumanitiesMedicinePhilosophy

Abstract

fetched live from OpenAlex

Actualmente Guatemala cuenta con una población de 13.344.770 personas que tiene una elevada tasa de población migrante, tanto nacional como internacional. Relacionado con el abuso de drogas, el país presenta la más alta tasa de consumo de mariguana en Centroamérica, y el consumo de cocaína se reconoce como un serio problema, que afecta mayoritariamente a los adolescentes y adultos jóvenes (15-30 años). Este estudio cualitativo y cuantitativo, describe la perspectiva de familias y familiares sobre los adictos a drogas ilícitas en Guatemala. La información recolectada proviene de personas referidas por la Línea de Crisis para drogas 1545. El estudio describe a la mariguana, seguida de cocaína y benzodiacepinas como las drogas de mayor consumo. Se detectó a la familia como el factor de protección más importante. Por otro lado, la respuesta de los servicios de salud es insuficiente; no existe en el país disponibilidad de iniciativas preventivas. Se recomienda realizar, en el futuro, otros estudios cualitativos y cuantitativos sobre este tema.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.301
Threshold uncertainty score0.599

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.024
GPT teacher head0.336
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations9
Published2009
Admission routes1
Has abstractyes

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Same venueRevista Latino-Americana de EnfermagemSame topicSubstance Abuse Treatment and OutcomesFrench-language works237,207