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Record W2912775890 · doi:10.15868/socialsector.33742

Doing Right Together For Black Youth: What We Learned From The Community Engagement Sessions For The Ontario Black Youth Action Plan

2018· report· en· W2912775890 on OpenAlexaboutno aff
Uzo Anucha, Sinthu Srikanthan, Rahma Siad-Togane Siad-Togane, Grace-Edward Galabuzi Galabuzi

Bibliographic record

Venuenot available
Typereport
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsnot available
FundersTechnische Universiteit Eindhoven
KeywordsPlan (archaeology)Youth engagementAction (physics)Action planBlack malePsychologyPolitical scienceSociologyPublic relationsGender studiesGeographyManagement

Abstract

fetched live from OpenAlex

Doing Right Together for Black Youth summarizes what was learned from over 1,500 community members who answered the call from the Ministry of Children and Youth Services (MCYS) to co-develop the Ontario Black Youth Action Plan (BYAP). The MCYS shared anonymized data (without any identifying personal information) captured at these community engagement sessions, as well as written submissions, with YouthREX to analyze, interpret, and summarize.This report shares the top ten issues for Black youth and their families, ideas on the best ways to engage Black youth in meaningfully shaping the development and implementation of the BYAP projects, as well as the important characteristics of organizations that can meet the needs of Black youth.

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)0.019
metaresearch head score (Gemma)0.015
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.140
Threshold uncertainty score0.462

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0280.010
Scholarly communication0.0080.004
Open science0.0020.011
Research integrity0.0030.006
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 head0.388
GPT teacher head0.391
Teacher spread0.003 · 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

Citations26
Published2018
Admission routes1
Has abstractyes

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