Bibliographic record
Abstract
s and Deeds/Nations that were crucial—as they were as well for critic John Bentley Mays. For Luis Jacob, Deeds/Abstracts was the point of departure for a discussion of aperture, of being open to the world. Jacob spoke for many of those present when he said “I am struck by the frequency in which this book has figured in discussions today. It’s evident that for the group today, this work is one of Curnoe’s most resonant” (Open Letter 2002: 84). In Prison Notebooks, Antonio Gramsci wrote that “The starting point of critical elaboration is the consciousness of what one really is, and is ‘knowing oneself ’ as a product of the historical process to date, which has deposited in you an infinity of traces, without leaving an inventory” (Gramsci 1971: 323). In the Curnoe archive, there is no record of him ever having read Gramsci, but certainly he would have understood this idea completely. As Curnoe said in the Deeds/Abstracts: The question of the power of histories of broad conclusions and great events in contrast to histories of details has occurred to me as I am writing this. I have felt the power of many details adding up to an understanding of the ground I am standing on. It is an understanding that is new to me, in spite of the fact that I have worked with this kind of information for years. (28) When Jamelie Hassan spoke of his Deeds/Nations as a “directory” (Open Letter 2002: 31), she made it clear that Curnoe’s seemingly endless collecting and
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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.015 | 0.015 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.027 | 0.003 |
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".