Update for Congress 2009: “Authority in the Past, Authority of the Past”
Bibliographic record
Abstract
As we reach another milestone, the Annual Meeting of the Canadian Historical Association becomes a little clearer. The inspiring but also terribly difficult process of evaluating proposals and drawing up a program is now complete. The core theme of the CHA meeting seems to have struck a chord and our program is littered with the concept of “authority”.We have an opportunity to open up some exciting discussions about different forms of authority, different practices that lay claim to be “authoritative”, and how we might navigate our archives with a heightened self-awareness regarding both authority in the past and authority of the past. Session and paper titles will signal where some of our discussions might be headed but I also hope the site and timing of our meeting is a dimension of all this.We shall be meeting in very difficult times for so many, both here in Canada and across the world. As some of the pillars of modern authority start to crumble, we historians might want to think about how we got here, but also how the here and now looks in (and at) the mirror of the past. Sitting in a capital city of one of the world’s G8 nation-states perhaps makes these discussions all the more urgent.
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 | 0.010 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.015 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.068 | 0.031 |
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".