Adelina Iftene: Prison Law and the COVID-19 Pandemic
Bibliographic record
Abstract
Join Zainab and Adelina Iftene, Assistant Professor of Law and Associate Director of the Health Law Institute, as they explore her research into prison law and the COVID-19 Pandemic. This interview follows topics from Professor Iftene's article in the Dalhousie Law Journal title "COVID-19, Human Rights and Public Health in Prisons: A Case Study of Nova Scotia’s Experience During the First Wave of the Pandemic".\nAdelina's past, current and upcoming major research projects investigate issues surrounding aging in Canadian penitentiaries; the regulation of health care provision in prisons; the regulation of end of life and medical assistance in dying in prisons; prison release mechanisms, in particular compassionate release; access to justice behind bars; and sentencing of older and sick individuals.\nYou can read Adelina's work here: Adelina Iftene, "COVID-19, Human Rights and Public Health in Prisons: A Case Study of Nova Scotia’s Experience During the First Wave of the Pandemic" (2021) 44:2 Dal LJ 477.
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How this classification was reachedexpand
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".