Bibliographic record
Abstract
The Tri-Council Policy Statement, which has its roots in the Nuremberg Code, specifies ethical obligations of Canadian researchers. The need for such regulations is evident in a number of studies which have shown complete disregard for the rights of human beings, studies which have continued into the current millennium. Teachers who conduct research in their own classrooms encounter ethical dilemmas in common with external researchers, but they also face unique challenges. Following a summary of 13 ethical issues facing educational researchers in general (e.g., students' ownership of their written work; anonymity vs. acknowledgment of accomplishments), this paper explores problems which are particularly troublesome for teacher-researchers: the ability of students to refuse to participate, and students' rights to the best instruction, be it experimental or control. For some types of teacher research, the problems surrounding informed consent can be addressed by having a third party manage the consent forms and data collection.
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 | 0.469 | 0.427 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.025 | 0.117 |
| Scholarly communication | 0.029 | 0.016 |
| Open science | 0.009 | 0.016 |
| Research integrity | 0.043 | 0.059 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".