“Surviving and Thriving”: An Autoethnography of a Black Afro-Caribbean Early Career Teacher in a Northern Ontario First Nation Community
Bibliographic record
Abstract
The beginning years of a teacher’s career can be an overwhelming experience, and combined with being in an isolated, fly-in community, particularly during a pandemic, can be debilitating. This qualitative research is aimed to support and account for the story of a Black Afro-Caribbean, early career teacher (ECT) in a Northern Ontario First Nation (FN) community over a three-year teaching placement. The goals were to use her stories for reflection, inspiration, and guidance to support other ECTs, and to provide recommendations to teacher-education programs to lessen attrition and increase retention among ECTs in FN school placements. An autoethnographic method was used to identify key themes in her narratives to better understand her experiences of surviving and thriving. Although this ECT was significantly tested about her decision to become a teacher, support, empathy, resiliency, and governing one’s practice with clearly defined moral and ethical principles rooted in the belief that every child can learn helped her survive and thrive. The conclusion was that ECTs in FN school placements need, among other things, a willingness to be vulnerable and resilient.
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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 | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 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".