Creating Model Citizens for the Information Age: Canadian Internet Policy as Civilizing Discourse
Bibliographic record
Abstract
In the late 1990s, the Government of Canada launched a string of initiatives to usher its citizens into the “information age.” Recently, the federal government has announced “mission accomplished” in its pledge to become a “model user” of information technology, recognized around the world as the country most connected to its citizens. This paper interrogates the term “model user” as a marker of the changes occurring to techniques of government in our expanding information society. It proposes that the “model user” represents ways to negotiate the changing relationship between nation, state, and citizen associated with economic restructuring and signals a new civilizing discourse for citizen conduct amid the dynamic flows of information and ideas. Further, the “model user” suggests an emphasis on innovation that is implicated within larger discourses of economic globalization and the premium placed on adaptability and creativity. Finally, this paper makes vivid the connections between the “model user” and emerging discourses of Canada as a “model democracy” and Canadians as “model citizens” within the global context.
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.058 | 0.040 |
| Scholarly communication | 0.031 | 0.012 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 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".