Appearance Before the Standing Committee on Citizenship and Immigration Re: National Identity Card
Bibliographic record
Abstract
has been in existence almost nine years. On its Web page, the following statement of purpose appears: [1] “Electronic Frontier Canada (EFC) was founded to ensure that the principles embodied in the Canadian Charter of Rights and Freedoms remain protected as new computing, communications, and information technologies are introduced into Canadian society.” It is inevitable that in the aftermath of crises such as September 11, concern for the security of the nation will (seem to) overweigh individual privacy rights. This government has introduced a number of bills that raise serious privacy issues and in the context of such legislation as well as the Canada Customs and Revenue Agency (CCRA) database on foreign travel activities and the Lawful Access Discussion Paper, the current proposal for an ID card strikes many that the government is clearly over-reacting. Simply put, Canadians neither need nor desire a National Identity Card. It is being advertised as a solution to identity theft and as means to improve the chances of identifying and apprehending terrorists. In addition, the convenience of a single piece of identification for facilitating the multitude of transactions that Canadians must deal with is also being promoted as an advantage.
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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.003 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.022 | 0.015 |
| Insufficient payload (model declined to judge) | 0.033 | 0.018 |
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".