Standpoint Theory in Professional Development: Examining Former Refugee Education in Canada
Bibliographic record
Abstract
On September 2, 2015, a toddler was photographed on an unnamed Turkish beach in a position reminiscent of a baby sleeping in his crib. Alan Kurdi would instantly become the poster child for an entire nation that had no other alternative but to run and risk their lives on inflatable dinghies. On the open expanse of the Mediterranean Sea, the rate of survival was much higher than staying in Syria. On December 11, 2015, the newly elected Canadian Liberal majority government opened up Canada’s borders to Syrian refugees, and the Canadian education system is now grappling with how to adequately address the needs of their former refugee students. This article examines how deficit discourse affects academic excellence of all English as an Additional Language (EAL) learners, including former refugee students, and how professional development offers a cost-effective solution to the effects of deficit discourse on former refugee students, while equipping teachers with reliable skills and tools to use in diverse classrooms. In addition, this article investigates how standpoint theory can be used as the foundation for professional development programming for teachers of all students, including those who were refugees. Keywords: education; deficit discourse; standpoint theory; refugee
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.040 | 0.015 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.001 | 0.005 |
| 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".