Technical Memorandum: A Training Evaluation Framework for PSTC MilObs Course
Bibliographic record
Abstract
Abstract : A current Applied Research Project (ARP) of DRDC-Toronto explores moral and ethical decision-making (MEDM) in Canadian Forces (CF) operations through field studies conducted at the Peace Support Training Centre (PSTC) in Kingston. CF personnel preparing to deploy as United Nations Military Observers undertake a number of training activities to enhance and develop their skills particular to Peace Support Operations (PSO). Through training, CF personnel receive intensive preparation, using a combination of classroom training and scenario-based training. One scenario-based exercise simulates a human rights violation - unarmed trainees attempt to negotiate the lives of civilians who are being verbally and physically abused by two armed police. Our program has examined a number of psychological processes during this scenario, such as aspects of moral intensity (physical proximity of the victim, MEFS I), emotion (MEFS II) and teamwork (MEFS III). The current work provides materials drawn from these studies. We created a set of PowerPoint slides that detail the most critical findings in the three field studies. Next, we generated a list of open- and closed-ended questions that trainees asked during the scenarios across all three studies (MEFS I, MEFS II, MEFS III). This list provides a means to underscore PSTC instruction to trainees, i.e., emphasizing the use of open-ended questions for eliciting situational awareness. Tables have been created that include specific examples of questions seeking both general and specific information. A separate table was constructed in which the common themes were extracted from the questions. The final section includes preparatory activities that lay the ground work for a PSTC training evaluation. Specifically, the evaluation is intended to explore how well the training translates into actual operational experience. This report concludes with possible next steps toward the evaluation and a plan for data collection.
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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 | 0.131 | 0.129 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.045 | 0.008 |
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".