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Record W7112462597

Repairing socioecological relationships: Landguaging the imperial L2 classroom

2025· other· en· W7112462597 on OpenAlexaboutno aff

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsViewpointsVariation (astronomy)Government (linguistics)Empirical researchFirst languageLanguage educationColonialismSelection (genetic algorithm)
DOInot available

Abstract

fetched live from OpenAlex

This two-manuscript dissertation explores how two imperial and non-Indigenous languages in Canada (English and French) can resist replicating monolingual and colonial traditions though plurilingual pedagogies and online tools. In Chapter 1, an overview of the ecolinguistic framework that all chapters are rooted in is presented. It explores how multimodal and plurilingual activities build learners’ relationships to their nested macro- to micro-sized socioecosystems. This framework is then extended to a discussion of ecological technologies and pedagogies. Chapter 2 (Manuscript A) focuses on the struggles that language learners experience when engaging with speakers of different language varieties. This difficulty is often explained by a lack of exposure to sociophonetic variability in classroom materials with the emphasis instead on teaching the (usually invariable) standard variety. Focusing on the French second language (FSL) context, our understanding of sociophonetic variation in the classroom comes primarily from textbook studies; little empirical evidence has quantified the amount and kind of social speech markers (e.g., age, race, region, native speaker status) found in FSL audiovisual curriculum. Using a comparative case study, this chapter examines the audiovisual materials of two FSL classroom contexts: the university and the government sponsored francisation course. Interviews and questionnaires elicited FSL instructors’ criteria for selecting materials, and their experiences with and attitude towards including social speech marker variation in their curriculum. Additionally, audiovisual materials from each instructor collected over a semester were categorized and analysed by five social speech markers and clip length. Results showed that instructors held positive viewpoints towards including variation; however, audiovisual materials from both settings were invariant across the markers of age, race, region, native speaker status and sourced mostly from mass media. Specifically, the materials excluded elderly, adolescent, children, racialized, non-native speakers and varieties from regions other than Québec. Suggestions for incorporating more varied materials in the curriculum are highlighted and form the basis of the second manuscript. To address the lack of variation found in the imperial L2 curriculum in Chapter 2, Chapter 3 (Manuscript B) introduces Parlure Games, a computer-assisted language-learning tool that promotes exposure to and interaction with those speakers absent from audiovisual materials (e.g., elderly, racialized) using non-mass media and online mapping. Parlure Games has three teaching goals: exposure to sociophonetic variation, development of plurilingual competencies, and opportunities to visualize and critically discuss imperialism’s territorial expansionism. Following a four-level chronological framework, Manuscript B reports on the first three stages: (1) the development of Parlure Games in alignment with high variability phonetic training (HVPT) methods; (2) an exploration of its pedagogical affordances based on ecolinguistic principles; and (3) its suitability for achieving the three teaching goals, as evaluated through the Technology Assessment Model-2 (TAM2). While the first two levels are conceptual and design-oriented in scope, the third is empirical: Drawing on TAM-2-informed data, seventeen undergraduate TESL teacher candidates rated Parlure Games highly, suggesting strong adoption intentions. Based on these findings and user feedback, we provide a revised model for the tool’s in-classroom implementation, preparing it for deployment for the final stage of the adopted chronological framework. In the final chapter, the main findings of each manuscript are reviewed, and the value of plurilingual ecolinguistic tools for enhancing the teaching and learning of imperial languages ecologically is reaffirmed. The studies’ limitations are outlined, followed by a set of plurilingual ecopedagogical, Landguaging activities that address the entanglement of language and land in imperial language teaching contexts, repairing imperialism’s sociecological relationship with land.

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)0.003
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 score0.040
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0160.014
Scholarly communication0.0100.005
Open science0.0020.014
Research integrity0.0020.002
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 head0.043
GPT teacher head0.296
Teacher spread0.253 · 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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