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
On Friday, 30 January 2015, Steven Blaney, Minister of Public Safety and Emergency Preparedness, introduced Bill C-51, also known as the Anti-Terrorism Act in Canada’s House of Commons. This article delineates research into the media coverage of Bill C-51 in the month after its introduction, prior to its legislation. A qualitative content analysis of 23 articles from five Canadian news sources ( National Post, The Globe and Mail, The Toronto Star, The Tyee, and rabble.ca) was conducted. Data were coded and analysed using the qualitative research software NVivo 10. Themes that arose from the data include: terrorism and our need for protection; production and reinforcement of fear; oversight, accountability, and abuses of power; and dystopic future and ‘big’ government. Findings show that the differences between alternative and commercial news sources were not as evident as much of the literature regarding the differences between the types of media would hypothesize.
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 | 0.004 |
| 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 | 0.001 |
| 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