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Record W7039808069

Narratives of Positive Impact by Canadian Muslims to Counter Islamophobia in High School Education

2025· article· en· W7039808069 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship at UWindsor (University of Windsor) · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Islamic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCompassionNarrativePower (physics)Presentation (obstetrics)ConversationIslamIslamophobia
DOInot available

Abstract

fetched live from OpenAlex

The goal of this project is to create a comprehensive pressbook that highlights the inspiring stories of Canadian Muslims who have made significant positive contributions to their communities. High school students can use the pressbook as a teaching tool, and it comes with thoughtfully designed lesson plans and quizzes to make learning interesting and educational. Driven by the pressing necessity to eliminate misunderstandings concerning Islam and its adherents, this project employs a qualitative methodology. By presenting their varied accomplishments and dispelling misconceptions, the pressbook aims to provide a comprehensive understanding of Muslim experiences in Canada. The project's conclusions highlight how personal narratives have the power to change people's perspectives. Not only do these narratives showcase the tenacity and accomplishments of Muslims in Canada, but they also offer a forum for positive discourse and compassion. This initiative fosters a more tolerant and understanding society by promoting inclusivity through the presentation of a range of narratives. To sum up, this pressbook project makes a substantial contribution to the conversation about inclusivity and cultural understanding. By including these tales in high school curricula, educators can give students the knowledge and compassion they need to confront stereotypes and actively eradicate Islamophobia. Following the guidelines, this abstract presents a thorough summary of the project's goals and wider societal implications.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.248
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.285
Teacher spread0.276 · 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.

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
Published2025
Admission routes1
Has abstractyes

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