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Record W2735128664 · doi:10.5539/elt.v10n8p63

On the Strategies of Graduation Thesis Writing Teaching of Translation Major Undergraduates Based on Eco-Translatology

2017· article· en· W2735128664 on OpenAlexvenueno aff
Lin Wang

Bibliographic record

VenueEnglish Language Teaching · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsnot available
Fundersnot available
KeywordsGraduation (instrument)BachelorMathematics educationIgnoranceConstructivePsychologyInterpretation (philosophy)EnlightenmentStatement (logic)Adaptation (eye)Selection (genetic algorithm)PedagogyLinguisticsEngineeringComputer scienceProcess (computing)Political scienceEpistemology

Abstract

fetched live from OpenAlex

Graduation thesis is an indispensible procedure for each undergraduate, which is crucial for successful graduation, employment, further study and even further development. However, due to most undergraduates’ ignorance of academic writing and the deficiency of current thesis writing course, thesis writing ability can hardly be enhanced and improved, accordingly, few good graduation theses can be produced among undergraduates. As a newly-launched major in recent a few years, translation major (BTI education, i.e. Bachelor of Translation and Interpretation) is also faced up with this problem. Eco-Translatology, a new theory combining ecology and translation studies, holds translation as adaptation and selection, which can also provide important enlightenment for thesis writing of translation majors. This paper, based on Eco-Translatology and current thesis writing course deficiency, aims to explore constructive strategies on how to give effective and efficient thesis writing course in hope of greatly improving thesis writing.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.600
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.043
GPT teacher head0.297
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2017
Admission routes1
Has abstractyes

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