Investigation and Research on MTI Dissertation Writing Mode in Hubei Province: A Case Study of the Dissertations of MTI Graduates at Four Universities
Bibliographic record
Abstract
This paper investigates and analyzes 122 dissertations of MTI graduates in 2015 in four universities in Hubei, develops a comprehensive understanding of the general dissertation writing mode of MTI students and carefully investigates a variety of problems: for example, there is only a small proportion of translation internship reports, experiment reports and research reports among their dissertations and the proportion of translation practice reports is much larger, accounting for 88% of the total number of dissertations; in translation practice reports, the proportion of studies on literary source texts takes up 37%; in addition, although many authors attempt to use a theory to criticize the translation practice of their own or other translators, they cannot really fully demonstrate the knowledge, interpretation and critical functions of theory and theory and practice are completely out of touch. The author of this paper believes that the main cause of these problems lies in some of these MTI departments. Faculty resources at some MTI programs are relatively tight; MTI internship practice is still a mere formality; its professional features have not yet manifested.
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.
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 | 0.000 | 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 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".