The piecing of identity : an autobiographical investigation of culture and values in language education
Bibliographic record
Abstract
This study will explore my own perception of my personal and professional roles as a language teacher in Nunavik and in Japan. In this qualitative study, I attempt to understand the negotiation of language and culture both in and out of the classroom. Using the autobiographical narrative method, I investigate questions about language and identity through my own personal lens and voice. My inquiry comprises two elements; it examines and interprets key episodes in my life as a learner and teacher, and as a researcher, I link these topics to theoretical and empirical knowledge. My narrative begins with the early years of my life as a Francophone immersed in an English neighbourhood in Montreal, grounding it in the particular experiences of my own learning and teaching. The study also includes a comparative analysis of my teaching experiences in Northern Quebec and in Japan. The journals I kept throughout my teaching assignments provide material for analysis which contributes a unique perspective to the body of literature addressing the relationship between culture, values, language and identity. I close the discussion with recommendations for the improvement of second language teaching and teacher development in intercultural contexts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.015 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".