Seeing linguistic systems as intellectual, aesthetic, and expressive achievements
Bibliographic record
Abstract
Linguists in the last century have asked how lexico-grammatical systems may or may not vary, due perhaps to their origins in human biology or sociality; as well as how they may reflect their genetic relationships or geographic distributions. But alongside seeing linguistic systems as instances of principles we may posit, it is also important to leave room for local contingency, and that includes seeing linguistic systems, to the fullest extent possible, as people's intellectual, aesthetic, and expressive achievements. Four steps are proposed in that direction: (i) striving for perspicuous descriptions of linguistic systems on their own terms in order to identify pervasive design or ‘genius’ across suites of features; (ii) exploring cases where unusual suites of features persist over time, where consistent choice and continuing intellectual, aesthetic, or expressive engagement with those features stand among possible explanations for their persistence; (iii) investigating speakers' creative engagement with lexico-grammatical features in verbal art and elsewhere, emphasizing dialectical relationships that tend to form as creative practices and suites of features affect each other, and then gauging how these relationships might shape linguistic systems over time; (iv) examining degrees of awareness, attention, and purpose when considering people's creative engagement with lexico-grammatical systems and their implications for how we understand linguistic systems as creative achievements. Two extended examples are considered: the multimillennial persistence, across all of its branches, of an unusual lexico-grammatical design or genius in the Unangan-Yupik-Inuit language family, suggesting the ongoing renewal of a particular set of aesthetic or expressive sensibilities; and the work of Eastern Chatino speakers to gain and teach awareness of the extraordinary systems of tonal lexico-grammar across Eastern Chatino varieties and how that awareness, helped in part by their work as linguists, has led to intellectual and aesthetic engagement with tone in the context of an ongoing social and political struggle for Indigenous language recognition and maintenance.
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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.054 |
| Scholarly communication | 0.014 | 0.014 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".