Differential Discourse Patterns in Mainstream Versus First Nations Students in an Adult Basic Education Classroom
Bibliographic record
Abstract
The purpose of this study was to record and transcribe a lesson conducted in the Initiation-Response-Evaluation (IRE) style, in order to examine the patterns of interaction between teacher and students, focusing on ways in which the teacher differentiates between First Nations and non-First Nations students, and on ways in which their discourse differs. I chose to use one of my own classes, and to examine my own interactions, in order to discover my role in these student-teacher interactions. What differences can be seen in the quantity and quality of student utterances between First Nations and mainstream students? How do I, as the teacher, treat students, and do I treat First Nations students differently? What am I doing that may cause differences, and how do I react to differences? How does the IRE style of the lesson impact upon student contributions? What is occurring that maintains or reinforces inequalities of knowledge and skills? In sum, I wanted to examine my role in the classroom more closely, in the hope that I could use any findings to improve my practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".