Bibliographic record
Abstract
While reflective writing is a common university task, it is often assigned without explicit attention to embedded cultural values and the linguistic features used to enact meaning. As yet, there is limited understanding of how values are built up throughout a reflective text and how such texts relate to the experiences they reflect on. This chapter examines this relationship in a reflective text from an Academic English course for international students in their first year of Arts studies in Canada which stood out from peer texts in its focus and framing. It takes as a case study one student’s reflective writing assignment on a speech, itself a personal reflection, by broadcaster Shelagh Rogers, an honorary witness to Canada’s Truth and Reconciliation Commission. Drawing on the Legitimation Code Theory dimension of Specialization and analytical methodology of cosmologies, this chapter reveals how constellations around the topic of ‘listening’ are assembled in each text and how they relate to valuing inclusive ways of understanding and interacting. This chapter provides insight into how constellations of values are framed and reframed within reflective writing, and how they shape and are shaped by cultural context and pedagogy towards a more holistic appreciation of reflective practices.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.029 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".