Bibliographic record
Abstract
learning experience for grade 6, 7, and 8 mathematics teachers in the Greater Toronto Area during the 2003-2004 school year that combined periodic face-to-face day sessions with weekly online discussions and activities. This document reports on evaluation findings in five main areas: (1) the program’s impact on teachers; (2) its impact on students: (3) its impact on students of different socio-economic (SES) backgrounds and abilities; (4) other intended and unintended effects of the program: and (5) issues related to the program’s sustainability and transferability. The evaluation methodology included pre- and post-program surveys of participating teachers and their students, classroom observations, interviews of program leaders and facilitators, and analyses of online activities. Findings suggest that teachers, on the whole, benefited from the program by developing greater confidence to teach mathematics; they became more committed to reflecting on their pedagogy now and in the future; they have begun to collaborate more with colleagues in some instances; they are implementing in their classrooms the three-part lesson strategy introduced during the program; they have introduced manipulatives, games, and technology into the curriculum, although in some of the classrooms in which we
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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.583 | 0.437 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".