Analogy, automation and diagrammatic causation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
One areal feature of East and Southeast Asian languages is the grammaticalization of an augmentative-diminutive pair from the nominals ‘mother’ and ‘child’, respectively (Matisoff 1992). Many Sino-Tibetan languages further grammaticalize noun-class affixes from these kinship nominals, adding a parallel ‘father’ analogy in the process. Some Tibeto-Burman (TB) languages further grammaticalize the resulting kinship trio into numeral classifiers and lexical and clausal nominalizers. This paper presents evidence from the Ngwi branch of Burmic demonstrating a novel, yet parallel, polygrammaticalization process involving ‘youth’ (from TB *lak) as an analogous lexical source. Data from 30 languages inform a gradient reconstruction of two integrated, parallel clines: a nominal suffix series, YOUTH > SPROUT > SLENDER > OBLONG > GENERIC, complemented by a numeral classifier series, YOUTH(S) > AFFINAL KIN > CONSANGUINEAL KIN > NARROW > GENERIC. Both paths underlie the emergence of a collectivizing clausal nominalizer. The results support an emerging consensus: Analogy, automation and diagrammatic causation are irreducibly interdependent components of grammaticalization.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it