Bibliographic record
Abstract
This is the last of three papers based on a 20-month study of teaching and learning in a diverse classroom in a downtown community school in Toronto, Canada. The purpose of the research was to describe the details of teaching and learning in a multicultural classroom and to document successful strategies in working with immigrant and minority students. The three papers detail the process by which this focus on classroom life led to a critique of the literature and to a new way to think about multicultural teaching and learning which I call narrative multiculturalism. In this paper, I explore the process of becoming a narrative inquirer in a multicultural landscape and the implications of this way of thinking on developing new kinds of understanding. I relate this experientially oriented work to new ethnographies and other work already finding its way into the field. I explore a narrative multicultural way of thinking in greater depth. I use my own work with a teacher participant to re-imagine multicultural life in schools and classrooms. The study demonstrates the potential contribution of narrative multiculturalism to understanding multicultural life and multicultural teaching and learning.
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 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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.030 | 0.025 |
| Scholarly communication | 0.017 | 0.009 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".