Bibliographic record
Abstract
That human (op)positions, contradiction and conflict, permeate our world is obvious; however, if, we (human beings) share a conceptual scheme, common to us all, how then we can agree and disagree, accept and reject, admit or repress, recognize and misrecognize so much in our worlds—between others and ourselves—is not obvious, or needs to be recounted. Notwithstanding, we want to reconsider our shared conceptual scheme—the necessities apart from which we cannot say what we ordinarily say, or even do. To be sure, the (op)positions result from these necessities. It is that sort of necessity, so to say, logic, or “what is common to us all,” that “we” want to describe, figure out or find out in ordinary language. To acknowledge a Cavellian insinuation: the necessities, being human, we must affirm and deny at once (i.e. the sense I sketch out from the epigraph above). In this essay, I claim that that is a dialectic inherent in ordinary language (in human forms of life).
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.058 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 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".