The distributional properties of long nominal compounds in scientific articles: an investigation based on the uniform information density hypothesis
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
Abstract Nominal compounds are a structure commonly used in scientific texts. Despite their commonality, very little is known about how they are distributed in scientific articles. Based on the Uniform Information Density hypothesis, which states that speakers communicate information at a constant rate, avoiding peaks and troughs of information transmission, we predict that nominal compounds should cluster toward the end of scientific texts, be preceded by supporting text that facilitates their understanding, and be repeated often after their first use. In this paper, we examine these predictions through a quantitative and a qualitative analysis of a corpus of scientific papers from the fields of Biology, Economics and Linguistics. While our investigation did not reveal definitive findings for the first and third predictions above, it did produce supporting evidence in favor of our second prediction, thus advancing our understanding of NC use and the choices speakers make when transmitting information.
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 | 0.002 | 0.008 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 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