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Record W2932376312

Peace, Poverty, and Privilege in Secondary School Settings: How Collaborative Research Informs Youth Human Rights

2019· article· en· W2932376312 on OpenAlexaboutno aff
Darlene Ciuffetelli Parker

Bibliographic record

Venue2019 Conference of the Canadian Society for the Study of Education · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsnot available
Fundersnot available
KeywordsMindsetParticipatory action researchPublic relationsSociologyPedagogyPrivilege (computing)General partnershipPovertyPolitical science
DOInot available

Abstract

fetched live from OpenAlex

This paper has its focus on peace, poverty, and privilege in secondary school settings in Ontario. The paper describes a collaborative research/practice network which seeks to enhance public confidence and the importance of a human rights framework for youth in secondary school settings. The research is guided by three principles: changing mindset; shifting practices; fostering youth voice, and parent engagement. By committing to a community of relational knowledge and practice, the network mobilizes knowledge via four intersecting areas of social justice, inclusivity, safe acceptance, and cultural competency. Reporting on evidence-based outcomes, the research identifies the following themes: a) climate, culture, and relationship; b) youth voice alongside caring teachers; c) stigma, image, acceptance, and resilience. Using a 3R narrative framework developed by the author that analyzed the data, the research collaborative informs a systems-based implementation plan based on three pillars of opportunity to: enhance professional practice and knowledge; build a culture of care, and; develop community partnership and relationship. This secondary school research implements deep knowledge and practice to and for wide-ranging school communities as well as for innovative reach in teacher education because it places, for the first time in Canadian poverty-school based research, youth voice at its center.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.462
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.033
GPT teacher head0.326
Teacher spread0.292 · 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 teacher head, 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

Citations0
Published2019
Admission routes1
Has abstractyes

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Same venue2019 Conference of the Canadian Society for the Study of EducationSame topicEarly Childhood Education and DevelopmentFrench-language works237,207