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Record W7133072754

Pathways for Decolonial FSL Literacies in Teacher Education

2025· dissertation· W7133072754 on OpenAlexaboutno aff
Nicole Isabelle George

Bibliographic record

VenueTSpace · 2025
Typedissertation
Language
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsTransformative learningPraxisIndigenousTeacher educationCritical pedagogyDecolonizationSocial justiceIndigenizationInstitutionalisationEquity (law)
DOInot available

Abstract

fetched live from OpenAlex

This research has been guided by an impetus for transformative educational change and a desire to broaden a vision for a renewed FSL (French as a Second Language) teacher education space. Within this broader context, I inquired about how French can be utilized as a decolonial language within French as a Second Language (FSL) teacher education, alongside the institutionalization of Indigenous Languages. Through the interplay of critical social justice education principles with educational praxis (Freire, 1972), Pathways for Decolonial FSL Literacies in Teacher Education (PaDFLiTE), a research-based pedagogical tool, was developed in response to two overarching imperatives: 1) to support transforming (educators’) self-awareness and praxis, and 2) to respond to the urgency to offer classroom implementation resources in support of decolonization. I have engaged with the concept of ethical spaces of engagement (Cree scholar Ermine, 2007) in support of UNlearning and RElearning, which are necessary for the emergence of new encounters between Indigenous and Euro-Western worldviews and pedagogies within the FSL teacher education space in B.C., extending to minority francophone settings, and beyond. This work supports the ongoing, multilayered process required in the current need to decolonize educational settings in Canada and beyond. This stance is reflected in its core social justice principle, which seeks justice and equity from a place of marginalization and systemic oppression, where Indigenous knowledges and ways of learning and being have been erased from the educational space. The eight modules also center on Indigenous authors’ work and scholarship. As a resource to propel future French settler teachers toward meaningful action, this research has demonstrated the pressing need to better equip future French teachers. It highlights the transformative power of teacher education. By empowering future French settler educators as agents of social change, this research contributes to an urgent call for an Indigenous-settler relational renewal (Donald, 2022) within the French educational space. As a minoritized and often marginalized language in Anglo-dominant contexts, I have proposed that a thoughtful engagement with PaDFLiTE can offer initial steps towards redefining the French language and teaching space as a more inclusive, diverse, and critically settler-aware language education space in an era of reconciliation. Globalement, cette recherche vise à explorercomment soutenir les enseignant.e.s. de français (FSL) actuels et futurs, à tailler un espace pour les perspectives et les pédagogies autochtones, là où dominent traditionnellement les théories, les textes et les approches plus euro-centrées et traditionnelles. Nous explorerons le contexte multilingue et multiculturel changeant, au niveau régional, provincial et national ainsi que des impacts sur l’enseignement et l’apprentissage du français en milieu M-12. Dans une perspective qui puisse reconnaitre et prendre en compte des complexités liées à l’enseignement du français, à la fois langue minorisée en milieu minoritaire, nous explorerons des implications pratiques potentielles dans un cadre qui soutient un engagement à la diversité, à l’inclusion et à la décolonisation. La relation entre les récits autochtones, les récits alternatifs et les approches ancrées dans l’enseignement du plurilinguisme et des multimodalités seront aussi explorées.

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)0.009
metaresearch head score (Gemma)0.013
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 score0.047
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0170.027
Scholarly communication0.0120.009
Open science0.0020.026
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0060.001

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 head0.021
GPT teacher head0.396
Teacher spread0.376 · 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
Published2025
Admission routes1
Has abstractyes

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