A Study of Teacher Candidates’ Views on Children’s Human Rights in Canada
Bibliographic record
Abstract
Abstract The purpose of the study was to adapt a pre-existing measure (Karaman-Kepenekci, 2006) to assess teacher candidates’ views about children’s human rights in Canada. Karaman-Kepenekci’s survey was originally administered in Turkey with results published in the International Journal of Children’s Rights. To benchmark our results against Karaman-Kepenekci’s findings, we adapted and administered the survey to a sample of 174 teacher candidates in Canada. Participants’ gender, age, ethnicity, experience with children and enrolment in a human rights course were measured. The psychometric properties of the adapted survey and teacher candidates’ views are reported. An exploratory factor analysis with direct oblimin rotation led to complementary but different results compared to Karaman-Kepenekci’s (2006) findings. In particular, two factors were found to underlie survey responses – one involving rights of children and another involving government responsibility. Hierarchical linear regression of factor scores indicated that, among participant characteristics, only gender and ethnicity were predictive of responses.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".