An Infection of Noble Causes: An Examination of the Effects of Noble-Cause Corruption on the Canadian Justice System
Bibliographic record
Abstract
Influenza does not usually pose a significant threat to one’s overall health. Most people who contract the seasonal illness can easily overcome their flu-like symptoms with over-the-counter medication. In some cases, however, influenza can expose a person to more serious bacterial infections like pneumonia. Pre-existing conditions, respiratory illness for example, increase the likelihood that infections like pneumonia will enter the body successfully, spread through the bloodstream, and trigger a multi-system infection (Ducharme, 2018). While such instances are rare, the results can be deadly. Noble-cause corruption is a form of corruption that occurs when individuals adhere to the problematic reasoning system of ‘the ends justify the means’ (Grometstein, 2005). Noble-cause corruption can be likened to influenza in the way that it affects the criminal justice system. We can think of it as an infection that causes the justice system to develop seemingly harmless ‘symptoms’ (or signs) of impaired function in the form of unit failures (Thompson, 2008). Pre-existing institutional conditions (Joy, 2006), like the tight coupling of crime-fighting units (Thompson, 2008), significantly increase the likelihood that more severe infections, such as socio-legal pressures, will successfully infiltrate the justice system and distort the conduct of individual agents. These factors work individually and together to produce consequences that are potentially lethal for due process and may result in wrongful convictions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".