Using Feedback to Conduct Crowd Control
Bibliographic record
Abstract
Crowd Control is a function generally associated with the police more than the military. However, the Canadian Forces are occasionally asked to intervene in riot situations either in Canada, in support to Federal, Provincial and Municipal Governments, or overseas, during Coalition operations. Thus, there is a need to understand crowd be-haviour and to determine optimal intervention strategies for crowd control. Arguably the most famous recent event involving the Canadian Forces was the Oka Crisis in 1990 in which Mohawk Warriors carried out a 76 day standoff and the Quebec Provincial Police were unable to handle the situation. Another example of situations concerning governments around the world are unruly protests during visits of foreign dignitaries, such as the Vancouver APEC Protest, in 1997. Although, the Canadian Forces have not been employed in these events, they have skills and resources that might be called upon if a situation gets out of control and must be prepared to deploy on short notice. A model has been developed that can be used to understand these events in the time dimension both inside the event and from event to event. The model has been devel-oped theoretically and “face validated ” using data from two case studies. The model is required to evaluate appropriate tactics such as the employment of non-lethal weapons, and as a training simulator for strategic and tactical commanders. 1
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".