Open Sharing of Data at a Canadian Neuroscience Institute
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Open sharing of research data is crucial to advancing our understanding of the human brain and discovering treatments for neuropsychiatric disorders. It is critical, however, to balance these goals with participant rights to privacy and confidentiality. We discuss the ethics of practicing open neuroscience at Baycrest Academy for Research and Education (BARE), a small but prominent Canadian neuroscience research institute based in a geriatric hospital. Through a systematic documentary analysis of applications for ethical approval, consent forms and study protocols, we report on data sharing trends and participant consent rates at the institute. We also provide actionable recommendations for institutes to support their researchers in sharing neuroscience data openly, ethically, and responsibly.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.052 | 0.253 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.013 |
| Science and technology studies | 0.003 | 0.016 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.108 | 0.174 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it