The 2009 Rotman-telus Joint Study on IT Security Best Practices
Bibliographic record
Abstract
This chapter describes the 2009 study findings in a series of annual studies that the Rotman School of Management at the University of Toronto in Ontario and TELUS, one of Canada’s major Telecommunications companies, are committed to undertake to develop a better understanding of the state of IT Security in Canada and its relevance to other jurisdictions, including the United States. This 2009 study was based on a pre-test involving nine focus groups conducted across Canada with over 50 participants. As a result of sound marketing of the 2009 survey and the critical need for these study results, the authors focus on how 500 Canadian organizations with over 100 employees are faring in effectively coping with network breaches. In 2009, as in their 2008 study version, the research team found that organizations maintain that they have an ongoing commitment to IT Security Best Practices. However, with the 2009 financial crisis in North America and elsewhere, the threat appears to be amplified, both from outside the organization and from within. Study implications regarding the USA PATRIOT Act are discussed at the end of this chapter.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".