LE MARCHE DE TRADUCTION AU CANADA ET AU NIGERIA : UNE ENQUETE COMPARATIVE
Bibliographic record
Abstract
In the present age which obviously, is well known for globalization, the fact that the world is growing more and more into a global village where connectivity takes place in real time is no longer debatable. So also is the need to facilitate communication and understanding among people and countries. Based on this, it will not be wrong to recall that translation has thus become an integral part of the modern society. Meanwhile, it is equally important to note that due to certain factors, translation practices differ from one country to another. The purpose of this paper is, first and foremost, to show the differences that exist in the translation industry obtainable in Nigeria and Canada, the two countries that we have chosen as case study. The main aim of the study which is analytical, comparative, informative and corrective in approach is to compare and contrast the situation in the two countries under study, with a view to identifying how one can be enriched through the experience of the other, thus contributing to the development of translation in the world.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.026 | 0.012 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".