The Empirical Assessment of English for Specific Business Purpose (ESBP) among Export Development Bank of Iran (EDBI) Staff
Bibliographic record
Abstract
The present study has been conducted with the purpose of exploring the relationship between EDBI staff's General English proficiency and their technical English Writing as well as the way each ESBP and GE courses affect their writing skill. The kind of the study is quasi-experimental with pre-test and post-test, being conducted among EDBI staff in Tehran Branches and Headquarters. In data collection two standard tests were used, namely Preliminary English Test (PET) for homogenous subjects, and also the level of their GE progress at the end of the treatment, and Business English Certificates (BEC) test Level B1, to measure their technical writing skill with appropriate validity and reliability. The findings indicate that: 1) there was a correlation between subjects’ general English proficiency and their business writing proficiency; 2) teaching writing of banking texts significantly improved EDBI staff’s General English; 3) teaching writing of banking could significantly improve EDBI staff’s Business English proficiency; 4) teaching writing of banking could significantly improve EDBI staff’s Business English proficiency more than GE proficiency.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".