The Job Analysis of Teaching Secretaries Working in an International Environment --- Taking Jinan University, Guangzhou, China as the Research Paradigm
Bibliographic record
Abstract
Under the guidance of national policy, Chinese higher education institutions use English as teaching language. With this feature, an international environment is formed that the university offers places to eligible students from all over the world and employs qualified teachers from all over the world to teach students. Working in an international environment, the teaching secretaries’ job is different. This paper analyzes the job particularity of teaching secretaries working in an international environment in higher education institutions that their working language is English and they have to work with teachers and students from all over the world, answer teachers and students questions and solve their problems related to teaching affairs. This paper proposes some effective measures from the personal aspect and university aspect to raise the quality of the teaching secretaries’ job. And this paper gets a conclusion that the teaching secretaries working in an international environment should increasingly improve their comprehensive quality, professional knowledge, and management skills.
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How this classification was reachedexpand
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 | 0.003 | 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 | 0.011 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".