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Record W2182687134

Impacts of a Peer Support Program for Street- Involved Youth 1

2011· article· en· W2182687134 on OpenAlexaboutno aff
Cheryl L. Currie

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsnot available
Fundersnot available
KeywordsPopulationPositive Youth DevelopmentYouth studiesQualitative researchPublic relationsSociologyCriminologyPsychologyGender studiesPolitical scienceDevelopmental psychologySocial science
DOInot available

Abstract

fetched live from OpenAlex

Homelessness is a growing problem in urban centres. The well-documented overrepresentation of Aboriginal peoples among the homeless in Canada makes it a particularly relevant issue for this population. Some of the most vulnerable homeless are youth who are at special risk for gang recruitment, prostitution, and exploitation. The Links program began in 2005 as a three-year project bringing street-involved youth and university students together to increase understanding, foster supportive relationships, and enhance the knowledge and skills of each group. Emphasis was placed on recruiting Aboriginal youth to the program. As a result 50% of street-involved youth who took part identified as Aboriginal. Qualitative evaluation data were collected via surveys, written assignments, and in-person interviews. Findings suggest the program created intense bonds between students and youth. Stereotypes were identified and broken down and youth were empowered to broaden their perspectives on what they could achieve. Both groups gained knowledge they can use to build a better future for themselves and their communities.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0010.004
Research integrity0.0010.001
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 head0.184
GPT teacher head0.452
Teacher spread0.267 · 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
Published2011
Admission routes1
Has abstractyes

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