Multilingual Versions of Popular Social, Emotional, and Behavioral Tests: Considerations for Training School Psychologists
Bibliographic record
Abstract
This paper focuses on bias in the translation of social, emotional, and behavioral tests. Specifically, the authors address tests developed in the United States (U. S.), but later adapted for use with non-English speakers, and / or individuals who live(d) outside of the United States. Ethics and best practices for use and selection of test translations are described, along with problems endemic to ad-hoc translation. In addition, the authors surveyed publishers to determine what languages and normative data have been made available other than the English version (with U.S. norms). This information is tabulated and presented. The most popular language available was English; normative data was available for English speakers from the United States, Australia, Canada, and the United Kingdom. Spanish was the second most popular, with 12.59% of the tests translated into Spanish (8.3% with norms). These Spanish norms may be general (all Spanish speakers) or specific (e.g., Puerto Rican norms). In addition, country-based norms are described for some tests, but the actual language is not (e.g., there are norms for Spain but it is unclear if the language is Castilian, Basque, Catalan, Galician, or Occitan).
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".