Thi Historians and Public Policy: Some Reflections based on a Visit to Canadian Peacekeepers
Bibliographic record
Abstract
A part-time member of the history department at Wilfrid Laurier University, I am also a Faculty Associate at the Laurier Centre for Military, Strategie and Disarmament Studies(LCMSDS). The purpose of the Centre is to “foster research, teaching, and public discussion of military and strategie issues of national and international significance.” Wilfrid Laurier is one of twelve universities across Canada which receive financial support from the Security and Defence Forum (SDF) of the Department of National Defence as part of its mandate to “develop a domestic competence and national interest in defence issues of current and future relevance to Canadian security.”
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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.012 |
| Science and technology studies | 0.085 | 0.035 |
| Scholarly communication | 0.020 | 0.007 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.010 | 0.015 |
| Insufficient payload (model declined to judge) | 0.011 | 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 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".