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Record W6901980841 · doi:10.60770/pvrv-bw85

Subjugated innocence

2024· article· en· W6901980841 on OpenAlexaffabout

Bibliographic record

VenueMRU-Repo · 2024
Typearticle
Languageen
FieldMedicine
TopicBiotechnology and Related Fields
Canadian institutionsMount Royal University
Fundersnot available
KeywordsInnocenceIntervention (counseling)IndigenousHuman traffickingWork (physics)Sexual abusePoison controlHuman factors and ergonomics

Abstract

fetched live from OpenAlex

In this comprehensive literature review, the author examines child sexual exploitation from a Canadian perspective. The focus was on understanding what Canada’s definition of human trafficking is, how Canada views the exploitation aspect and how that has translated into Canadian legislation. Victims of domestic child exploitation are almost always girls between the ages of 13-17 and most commonly Caucasian. This profile could be skewed by the clandestine nature of this crime and that what is known about victims is based only on police-reported data. Risk factors highlight that those who are most vulnerable are girls, Indigenous, runaway or throwaway youth and LGBTQ+. This literature review highlighted that there is a lack of understanding of how male youth, as well as Indigenous youth, are trafficked. It also highlighted that more is needed to be learned about the various forms of child sexual exploitation. The second half of this literature review was investigative, in that it aimed to learn more about prevention and intervention programming, including how they work and apply knowledge to create effective and holistic programming. It then concludes with overviews of some noteworthy programs that assist Alberta victims specifically.

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)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.496
Threshold uncertainty score0.986

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0040.008
Scholarly communication0.0060.003
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.006
GPT teacher head0.271
Teacher spread0.265 · 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 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

Citations0
Published2024
Admission routes2
Has abstractyes

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