Bibliographic record
Abstract
For as long as human beings have used it to organize and conduct their activities, writing has played an integral role in the creation, sharing, and contestation of knowledge.Tracing the intertwined history of writing and secular knowledge of civilizations in Europe, the Middle East, the Mediterranean, China, India, and Mesoamerica, and Europe, Bazerman and Rogers (2008a, b), for example, map out the complex ways in which writing has been instrumental to the formation of knowledge institutions, disciplines, and communities.In the last few decades, however, the question about the role of writing in the production of knowledge has gained new salience with the rise of what has commonly been termed the knowledge society, where civic life as well as much economic activity depend on the production and sharing of knowledge.Indeed, according to some estimates, knowledge accounts for about three fourths of the value produced in the knowledge economy (Neef, 1998, ctd. in Brandt, 2005), rendering it "more valuable than land, equipment, or even money" (Brandt, p. 167).And because much of this knowledge is created, shared, inscribed, contested, and used largely through various textual forms, writing has moved centre stage in all sectors of society.As Brandt (2005) observes in her study of writing in contemporary knowledge-intensive organizations, with its integral role in the production of knowledge, writing fuels the knowledge economy, with written products becoming Coe, R., Lingard, L. & Teslenko, T. (Eds.).(2002).The rhetoric and ideology of genre: Strategies for stability and change.Cresskill, NJ: Hampton Press.
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 | 0.020 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.015 | 0.084 |
| Scholarly communication | 0.025 | 0.033 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.008 | 0.014 |
| 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".