Boston Naming Test norms for the Dominican population
Bibliographic record
Abstract
Background: Although neuropsychology is a well-established discipline worldwide, in the Dominican Republic (DR), its practice is relatively new.Aims: This research was conducted with the aim of adapting and standardising the 2005, 60-item version of the Boston Naming Test (BNT) in the DR, taking into consideration the influence of gender, educational level and age.Methods & Procedures: The sample consisted of 239 Spanish-speaking, healthy community-dwelling Dominicans between 16 and 80 years of age from each of the country’s major provinces.Outcomes & Results: Results indicate that, of the demographic variables studied, the educational level alone influences performance on the naming test.Conclusions: We recommend a change in the presentation order of the original BNT items to respond to the intended increase in difficulty. The use of these norms will facilitate interpretation of the results not only for Dominicans in the DR but also for first-generation Dominicans who live in other countries like the United States, Canada, and Spain, where there are sizeable Dominican communities, helping to adequately classify performances as normal or pathological.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".