“Man plans,<scp>G</scp>od laughs”:<scp>C</scp>anada's national strategy for protecting critical infrastructure
Bibliographic record
Abstract
Abstract Critical Infrastructure Protection seeks to enhance the physical and cyber‐security of key public and private assets and mitigate the effects of natural disasters, industrial accidents and terrorist attacks. In 2009, severalCanadian governments published theNational Strategy and Action Plan for Critical Infrastructure(NS&AP), a framework for governments and the owners and operators of critical infrastructure – largely in the private sector – to collaborate on the security and increased resiliency ofCanada's critical assets. Drawing on the social science risk literature, audits, and a three‐year research and education project, this article argues that the strategy of relationship building, collaborative risk management and information sharing is under‐developed and limited by market competition, incompatible institutional cultures, and legal, logistical and political constraints. TheNS&APshould better delineate risks and identify how governments can work with industry, and acknowledge the paradox between trust and transparency, the role of small‐ and medium‐sized enterprise, and how risk management processes can vary.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.048 | 0.009 |
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".