Bibliographic record
Abstract
Borderland school, narratives of teaching in, 62-63 Borders, 54 Canada's Multicultural Act (1988), 141 Canadian school system, 199 Canadian teacher, 199 learning about Japanese schools through lens of, 183-184 schooling in one's own culture forms foundation to building knowledge, 183 sense of observations from Canadian teacher perspective, 182-186 understanding of schooling as complex intersection of school and society, culture and curriculum, 183 Causality, illusion of, 120 Chilean, 33-34 Classroom management supported by group-oriented society, 180-181 Classrooms, 17-18 Co-participant, author as, 106 College Entrance Examination, 149 Communities, schooling in one's own culture forms foundation to building knowledge about schooling in other, 183 Comparative education research studies, 192-193 Conceptual curricular framework, my story as student reconstructed through, 154-157 Constraints, 57 Consumer rights, 104 Conversational education.See Problem-posing Cosmopolitan citizenship, 102-103 Cree teachers and students, experiences of, 136-137 Critical race theory, 135 Critical service-learning, 81-82 Cross-boundary children, 55 Cross-cultural chickens and eggs crossing to new culture, 16-22 crossing to our home culture, 22-23 data analysis and discussion, 16-24 educational significance, 24-25 enduring puzzles, 23-24 literature supporting my investigation, 14-15
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.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.537 | 0.340 |
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".