Bibliographic record
Abstract
Chapter 4 acknowledges that even when we are successful at re-enchanting multilingualism, dis-alienating ourselves from “linguanomics” (Hogan-Brun 2017), and delinking from lingualism, monolingualism will nonetheless remain powerful in various forms and intensities, and many of us will remain responsible for its sedimented historical effects on people in our midst. The chapter wagers that the period from now until 2040 constitutes the remainder of what I consider to be an era of late mono/lingualism, a period we might date to the 1948 ratification of the Universal Declaration of Human Rights in the Palais de Chaillot in Paris (Kellman 2016). With more than 600 legally equivalent linguistic versions, the UDHR was an unprecedentedly “omnilingual aspiration” (ibid), which garnered criticism for overreach from Saudi and Iranian spokespeople at the time, as well as from the American Anthropological Association. Such omnilingual ambitions intensified in the 1970s and 1980s with customs deregulation and the implementational phase of neoliberal economic policy, and saw a chaotic, asymptotal boom in the 1990s with algorithmic corpus-driven Machine Translation.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".