Report and Expert Testimony on rigorous forensic psychological assessment practices to the Joint Federal/Provincial Commission into the April 2020 Nova Scotia Mass Casualty
Bibliographic record
Abstract
We relied on the principles of open science in the preparation of this report. Open science aims to increase the openness, integrity and reproducibility of science by making research, data, and their dissemination available to all. Transparent science enables critical review, verification, and ultimately improved quality of work. These ideals are particularly important in legal and forensic work where law and policy that affect people’s lives are involved. Our approach to open science in this report involved extensive referencing of our opinions and the sources relied upon, citation using digital object identifiers (DOI) where available, explicit disclosure of relevant alternative views and disagreements, and sharing information about the terms of reference, project timelines, and communication with the Commission in the report. We also created a page on the Open Science Framework for this project to make available any documents that should be publicly accessible but are not easy to access (e.g., an ethics document we cite frequently that is otherwise difficult to access) as well as our report itself (both parts I and II), and a link to our expert testimony to the Commission.
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 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 | 0.012 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.052 | 0.023 |
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; both teacher heads 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".