Securing the Brisbane 2014 G20 in the wake of the Toronto 2010 G20: ‘Failure-inspired’ Learning in Public Order Policing
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Extending inquiries into the dynamics underpinning the ‘iterative’ development of security governance at mega-events, this article explores practices of knowledge sharing and policy transfer at major political summits. Through detailed interviews with police involved in the Toronto 2010 G20 and the Brisbane 2014 G20 summits, and through analysing supporting documentation, we examine the ways in which police interpret past events, as either ‘failures’ or ‘successes’, specifically in the context of public order policing. The article extends insights into how such perceptions are facilitated through transnational exchanges, particularly where event-related ‘failures’ might be considered as a benchmark for iterative policy developments. We explain this process as a form of ‘failure-inspired social learning’ that questions the effectiveness, norms and legitimacy of established policies, practices and institutions involved in security governance, which can influence future transformations in global ‘best practices’.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it