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
This study investigates the effects of topical knowledge on ESL (English as a Second Language) writing performance in the English Language Proficiency Index (LPI), a standardized English proficiency test used by many post-secondary institutions in western Canada. The participants were 50 students with different levels of English proficiency (basic, intermediate, and advanced) attending a Canadian college. Each student wrote two timed-impromptu essays: one responding to a prompt requiring general knowledge about university studies and the other pertaining to specific knowledge about federal politics. Results showed that students across three proficiency levels performed significantly better on the general topic than they did on the specific topic. The specific topic produced lower scores on content due to poor quality and development of ideas, implicit position taking, and a weak conclusion. Students also scored lower on organization and language on the knowledge-specific task because of weaker coherence and cohesion, shorter essays, more language errors, and less frequent use of academic words. Post-test interviews confirmed that participating students were challenged by the prompt that required specific topical knowledge. The study draws attention to the importance of developing appropriate prompts for ESL writing tests.
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 | 0.000 |
| 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