The New Requirement for Instructor Recruitment at School of Foreign Languages: What Do Administrators Think?
Bibliographic record
Abstract
In 2018, a legislative change -law number 2547- resulted in the adoption of the title "instructor", replacing "lecturers, specialists, translators, and education planners" for positions at the different departments of universities. This law also led to an adjustment in the instructor recruitment requirements. Correspondingly, the English language teaching instructors must have completed a master's degree to be hired to work at School of Foreign Languages (SFLs). This paper aims to uncover the opinions and suggestions of School of Foreign Language administrators about this change. This study shows that administrators approach the new requirement unenthusiastically due to the possible problems in hiring instructors. As an alternative criterion to a master's degree in ELT, administrators consider certification, teaching experience and graduate degrees in non-ELT programs. The results suggest that instructors be provided with professional development opportunities that merges theory into practice.
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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 | 0.037 | 0.061 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".