MétaCan
Menu
← Back to cohort
Record W302600204 · doi:10.12794/metadc407816

The Effects of a Human Trafficking Prevention Workshop Package on Participant Written and Simulation Responses

2013· dissertation· en· W302600204 on OpenAlexaff
Tiffany P. Sayles

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsGlobal Affairs Canada
Fundersnot available
KeywordsHuman traffickingComputer scienceData sciencePsychologyCriminology

Abstract

fetched live from OpenAlex

This study evaluated the effects of a community workshop designed to teach community members about human trafficking prevention. Participants were trained to identify the critical and non-critical features of human trafficking and safe ways to respond to identified trafficking situations. A pre-post treatment design was used to assess the effects of a community workshop across written and verbal target behaviors. This included written responses as well as simulation assessments across five different trafficking scenarios. Results indicate that all participants engaged in more correct responding within the written assessment and asked specific relevant questions with greater confidence within the simulation assessment following training. However, social media and empathy responses following the workshop did not differ from baseline. This study is one of the first empirical studies aimed at formally evaluating the effects of human trafficking prevention workshops. Results are discussed in the context of instructional design, measurement of outcomes, and interdisciplinary collaboration.

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)0.011
metaresearch head score (Gemma)0.057
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.057
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.039
GPT teacher head0.384
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

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 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

Citations0
Published2013
Admission routes1
Has abstractyes

Explore more

Same topicSex work and related issues→French-language works237,207→