LE MARCHE DE TRADUCTION AU CANADA ET AU NIGERIA : UNE ENQUETE COMPARATIVE
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.004 | 0.001 |
| 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 it