Bibliographic record
Abstract
This article is part of a special Left History series reflecting upon changing currents and boundaries in the practice of left history, and outlining the challenges historians of the left must face in the current tumultuous political climate. This series extends a conversation first convened in a 2006 special edition of Left History (11.1), which asked the question, “what is left history?” In the updated series, contributors were asked a slightly modified question, “what does it mean to write ‘left’ history?” The article charts the impact of major political developments on the field of left history in the last decade, contending that a rising neoliberal and right-wing climate has constructed an environment inhospitable to the discipline’s survival. To remain relevant, Palmer calls for historians of the left to develop a more “open-ended and inclusive” understanding of the left and to push the boundaries of inclusion for a meaningful historical study of the left. To illustrate, Palmer provides a brief materialist history of liquorice to demonstrate the mutability of left history as a historical approach, rather than a set of traditional political concerns.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.030 |
| Scholarly communication | 0.013 | 0.018 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 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".