Bloody Wednesday in Dawson College - The Story of Kimveer Gill, or Why Should We Monitor Certain Websites to Prevent Murder?
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
The article deals with the Dawson College Massacre, focusing on the story of Kimveer Gill, a 25-year-old man from Laval, Montreal who wished to murder young students in Dawson College. It is argued that the international community should continue working together to devise rules for monitoring specific Internet sites, as human lives are at stake. Preemptive measures could prevent the translation of murderous thoughts into murderous actions. Designated monitoring mechanisms of certain websites that promote violence and seek legitimacy as well as adherents to the actualization of murderous thoughts and hateful messages have a potential of preventing such unfortunate events. Our intention is to draw the attention of the multifaceted international community (law enforcement, governments, the business sector including Internet Service Providers, websites' administrators and owners as well as civil society groups) to the shared interest and need in developing monitoring schemes for certain websites, in order to prevent hideous crimes.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it