Bibliographic record
Abstract
The debate that might have developed in Canadian historiography, about how new tools from social semiotics and cultural studies could be deployed both by socialist historians and by those asking newer, less class-based questions, never did happen. Instead, what appeared in print was invective. The impression was created that to be theoretical was to be anti-labour history and anti-Marxist, and young progressive historians tended to conclude that, if they wanted to ask the “old” questions about class power, women’s oppression, and imperialism or racism, there was no need to read any theory. The potential for a number of overlapping debates on key methodological issues was thus wasted. The new social history gave us a number of new tools to do research, but the sophistication in research methods was generally employed to explore some rather simple (if important) research questions. The basic question driving socialist feminist inquiries as well as Marxist ones was: whose interests are served? The author explains her conclusion that it may be more productive to put inquiries into interests temporarily on hold, and experiment with questions that focus on effects.
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 | 0.033 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.017 | 0.040 |
| Scholarly communication | 0.020 | 0.019 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.008 | 0.013 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".