Unpacking Our White Privilege: Reflecting on Our Teaching Practice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
MacIntyre (1981) asks, “Of what stories do I find myself a part?” (p. 201). As teachers working in an Indigenous context, we found ourselves telling stories that had moments of tension between our Eurocentric ways of knowing and the Indigenous context in which we taught. This intersection has prompted our research. We ask two questions in this inquiry: What can our experiences as non-Indigenous teachers in an Indigenous community offer us in our understanding as new researchers in the field of Indigenous education, and how can our teaching narratives further preservice teachers’ understandings of teaching Indigenous students? Through critical White studies, our research examines White privilege, power, and position and begins to unearth the experiences of teaching as non-Indigenous educators in a remote Indigenous community in Ontario, Canada. Narrative inquiry and autoethnographic methods connect our stories to greater social, political, and cultural discourses. These stories serve to disrupt the dominant discourse that divides and others the complexities of Indigenous education. This work will interrogate and unpack our White privilege and power and will serve to assist preservice teachers in their understanding of teaching within Indigenous contexts.Keywords: Indigenous education; narrative inquiry; critical White studies; teacher education
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.
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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it