Bibliographic record
Abstract
A recent book, Contemporary Democratic Theory, is about the decline of democracy. Not an explanation of the phenomenon, but rather a look at how democratic theory has responded. This paper adapts that approach. The context of progressive librarianship (PL) has likewise shifted and consolidated with the results of the 2024 US presidential election and its aftermath. This is not localized or short term, it is global and persistent—and for democracy as well as libraries. The time has come to step back and ask the equivalent questions to that book on democratic theory: what is PL now? How did PL adapt and how might PL adapt? Efforts to document the work of and define PL began in response to “considerable ambiguity about just what constitutes progressive librarianship”—an inquiry conducted over the course of 15 years. It revealed that PL is an umbrella term describing both scholarship and organizational activities, gathering together many labels, if not always comfortably. This paper traces those paths, and based on that history suggests ones for PL to take, and perhaps as important, not to take.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.010 | 0.030 |
| Scholarly communication | 0.017 | 0.021 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".