Cross-cultural perceptions of teachers’ responsibilities towards fostering meaningful relationships with students: a glimpse at Canada and Japan
Bibliographic record
Abstract
The guidance teachers provide in the school environment reaches far beyond the scope of content delivery. To promote student achievement, they become mentors and leaders, embracing non-instructional roles to better understand student needs and effectively support them in reaching goals (Ayers, 2010; hooks, 2003). To gain a deeper understanding of the factors and influences that impact student outcomes and success, I embarked on a research study that examines the relationship between school personnel and the student. Beyond Ontario classrooms exists a wide array of celebrated pedagogical strategies. My time working as a high school English teacher in Shizuoka, Japan from 2011 to 2014, exposed me to an educational system unlike the one I experienced growing up in Toronto, Canada. I conducted a cross-cultural research study of the student-teacher relationship in two vastly different yet renowned educational frameworks found in Canadian and Japanese schools. I interviewed four experienced high school teachers—2 in Canada and 2 in Japan—on how they perceive and exercise responsibilities towards fostering meaningful, mentoring relationships with students both inside and outside of the classroom. Findings highlight similarities and differences in approaches towards educating the whole student in the diverse cultural contexts. Results indicate key differences in structurally integrated mentorship versus embracing the role from personal willingness.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.023 | 0.008 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 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".