Deconstructing the Translation of Psychological Tests
Bibliographic record
Abstract
The translation of psychological tests has become widespread as the globalization process has led to testing instruments designed in one country being applied in a different one relatively quickly, since it is less expensive and faster to adapt an existing instrument than to devise a new one in another culture. In order to provide a fully functional version of a test in a different language and culture, the whole cultural context within which a particular test is to be used must be considered, and it is not certain that this has always been the case. This review article explains the peculiarities of psychological tests as a genre and documents the process of translation which has traditionally been used. It is shown that while psychologists have increasingly become aware of the role of cultural context, they have mistakenly regarded this as an issue which is separate from the translation process. That concern for the cultural context is part and parcel of translation itself, is illustrated both in modern translation theory and in current translation practice.
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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 | 0.064 | 0.131 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.003 | 0.029 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".