A Contrastive Study on the Thematic Structure Functions of English and Arabic Short Stories
Why this work is in the frame
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Bibliographic record
Abstract
Charles Dickens’s (1909) “Little Dorrit” and Al Tayeb Saleh’s (1997) “Nakhla Ala Al Jadwal” were the subject of this investigation. Using Halliday and Matthiessen’s (2014) model of thematic categorizations and functions, this research paper examined thematic structure functions in relation to Dickens’s and Saleh’s short stories. Hence, 234 English and 304 Arabic clauses were manually extracted from the short stories and analyzed regarding the proposed framework. The findings revealed that the use of topical themes was the highest and the interpersonal was the lowest in frequency while the textual themes were at some point in between the topical and interpersonal ones. The comparison also had no bearing on the topical themes because they were identical, but the textual and interpersonal themes recorded distinct results. In Arabic, the utilization of textual themes was higher but the implementation of interpersonal themes was more employed and exercised in English. Each of which indicates multifarious reasons and functions to be regarded to the author’s vantage point.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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