Psychometric properties of an Icelandic translation of the Basic Personality Inventory / Throstur Byorgvinsson.
Bibliographic record
Abstract
This study investigated the psychometric properties of an Icelandic \ntranslation of the Basic Personality Inventory (BPI), using a sample of \n609 Icelandic teenagers. The translation procedure is described \nthoroughly in order to provide the reader with a basis with which to \nassess its impact on establishing an equivalent version. The Icelandic \nBPI item and scale characteristics are compared with available North \nAmerica results. With only one exception a comparison of the scale \nmeans between Iceland and Canada, revealed between-country \ndifferences with the same magnitude as between provinces within \nCanada. The results from inter-item consistency measures, correlation \nmatrices, and test-retest reliabilities are similar in both countries. The \nfactor structure of both the Icelandic and the original version of the BPI \nis identical. The results from this initial study are promising in \nrevealing a high degree of correspondence between psychometric \nproperties of the Icelandic BPI and the English BPI. This is a promising \ninitial indication that the existing empirical/clinical results with the \nEnglish version of the BPI will be relevant to the Icelandic version.
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.
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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".