Bibliographic record
Abstract
ONE OF THE MOST interesting aspects of the reaction to Canada: A People’s History has been how divergent it is, and I thought it might be useful to examine some of these differences in the hope of making a little headway in the continuing dialogue about the popularization of history. The series has been a major hit with the television audience in Canada. In the first season, each episode had an average audience of 1.2 million on the CBCs English network and 360,000 on Radio-Canada; when repeat broadcasts are included, the weekly total is more than two million. One of our main goals in making the series was to reach a mass audience to prove that Canadian television viewers would sit down week after week to watch what is, in television terms, a fairly dense two-hour programme on a serious subject and these figures indicate that we exceeded our fondest expectations. The ancillary products have done equally well: the first volume of the series companion book has sold about 65,000 copies (as well as winning a
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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.082 | 0.032 |
| Scholarly communication | 0.017 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.010 | 0.013 |
| Insufficient payload (model declined to judge) | 0.011 | 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".