RUNNING HEAD: Annotated Bibliography
Bibliographic record
Abstract
The purpose of this document is to develop an annotated bibliography of resources that represented the diversity of the Ontario science classroom. Many teachers consult different resources when developing their lesson plans and teaching their classes. However, not many of these resources cater to all students, especially to visible minorities. We were especially concerned about students from groups that have traditionally been under-served or under-represented in science and technology. As a result, we have compiled a list of resources, such as websites, books, journal articles, etc, that would accomplish this goal. We hope elementary teachers will refer to our bibliography when they develop and/or teach their classes. High school teachers will also find this bibliography useful in developing their lesson plan, especially the section on science and ethics, since many of the resources are generally applicable. Common Questions about the Bibliography: 1. How can the bibliography be used? Teachers can use this bibliography in multiple ways. For example, they can locate the
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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 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.043 | 0.086 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.287 | 0.159 |
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".