What is my Child Learning at Elementary School? Culturally Contested Issues Between Teachers and Latin American Families
Bibliographic record
Abstract
This study is part of an extensive research project on children of Latin American immigrants, their teachers and families. Through participant observation in one designated Canadian school, we captured the perspectives of ten students, their parents and teachers. An additional thirty-five families from other elementary schools in Toronto were interviewed to test the trustworthiness of the initial analysis. From the stories of these families and our knowledge of their children's schools, we describe how the parents' practices interact with mainstream practices and how the former are constructed within the present school system. Findings reported include: 1) Issues in communication involved teachers' use of educational terms that the parents did not understand. Teachers' positively slanted reports of the children's progress were not understood as indicating the genuine weakness of the child's performance. 2) In most cases, the family's support was not effective in helping children improve their grades at school, and this resulted in family conflicts and parents becoming disengaged from their children's academic tasks. 3) Children and parents expected a more personal approach than the teachers provided. It is concluded that a critical interrogation of the structures of educational delivery is needed as well as attention to the perceptions, beliefs, goals and knowledge of minority parents.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.012 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| 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".