Variations in Textualization: A Cross-generic and Cross-disciplinary Study, Implications for Readability of the Academic Discourse
Why this work is in the frame
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Bibliographic record
Abstract
According to discoursal views on language, variations in textualization strategies are always socio-contextually motivated and never happen at random. The textual forms employed in a text, along with many other discoursal and contextual factors, could certainly affect the readability of the text, making it more or less processable for the same reader. On the basis of these assumptions, the present study set out to examine how our data varied across genres and disciplines in terms of our target textual forms. These forms are as follows: the magnitude of T-unit (MOTU), the degree of embeddedness of the main verb in T-unit (DE), the physical distance between the verb and its satellite elements (PD), the magnitude of the noun phrase appearing before the verb (MOX), and the magnitude of noun phrase appearing after the verb (MOY). Our data consisted of 20 research articles randomly selected from two different disciplines of Biology and Applied Linguistics, to be analyzed in terms of the above-named textual strategies. One way ANOVA and post hoc Tukey tests were used for data analyses. The results revealed cross-generic as well as cross-disciplinary differences in the employment of the above textual forms. These findings were discussed in terms of the academic concepts and discourse on the one hand and the possible effect of the required textual forms on the readability of the text on the other hand.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.004 | 0.002 |
| 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