The understated role of pedagogical love and human emotion in refugee education
Bibliographic record
Abstract
This study sought to determine the role pedagogical love can play in the emotional experience of (Arabic-speaking) refugee families in Calgary, Canada, as they engaged with the public education system at the Grade 4–12 level. Through a cooperative inquiry approach, based on a shared agenda and interests, the researchers used cycles of action and reflection to elicit and analyse the experiences of parents, teachers, and in-school support workers. Contextualized within a LEAD (Literacy, English, and Academic Development) program, the study triangulated data from focus groups comprising Syrian and Iraqi Arabic-speaking families, educators, and settlement workers. Specifically, participants in the LEAD program were invited to articulate how pedagogical love could serve as an overarching orientation in making educational transition as successful as possible for refugee families. Using Braun and Clarke’s thematic analysis, the researchers analyzed data in the form of reflections from parents, educators, and in-school support workers. Based on these data, we extrapolated four interconnected themes that demonstrated the positive correlation between incorporating pedagogical love into the classroom and refugee families’ educational experience: (1) promoting pedagogical love through empathetic outreach; (2) promoting pedagogical love through increased societal exposure; (3) promoting pedagogical love through flexibility, trust, and confidence; and 4) promoting pedagogical love through individualized care.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.029 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".