Bibliographic record
Abstract
Can or should the history of science have a master narrative? This is a question that has exercised the minds of many historians since the Strong Programme questioned the deep connection between a sort of philosophical success story and the nitty-gritty of scientific work. 1 Since the 1970s, most of the historians of science have spent our time in the microhistorical trenches, creating thick descriptions, examining winners and losers, problematizing all the events and labels we had handed us by the likes of Herbert Butterfield, whose Origins of Modern Science presents an interesting contrast with his Whig Interpretation of History (but more of this later). 2 And yet, as we taught our survey courses, many of us ended up relying on Stephen Mason's A History of the Sciences, first published in 1953 and in print until the 1990s. To some extent, Mason avoided the problem of the master narrative by having no narrative at all-the text was often encyclopaedic; but it was clear that the organizing principle was based on the triumph of modern physical science. Herein lies the paradox of history: master narratives may become Whiggish by making the past a stairway to the present, while micro-histories may turn the past into a series of random acts without meaning or larger significance. The discussion of the place of the "Big Picture" in the history of science reoccurs with a certain regularity, with the British Journal for the History of Science devoting a whole issue to the topic in 1993, and Robert E. Kohler raising the issue in Isis in 2005.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.016 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".