The Mini-IPIP6: Validation and extension of a short measure of the Big-Six factors of personality in New Zealand.
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
This study extends the Mini-IPIP, a short measure of the Big-Five personality dimensions, to a Big-Six model of personality structure based on the HEXACO. Exploratory and Confirmatory analyses of a representative New Zealand sample (N = 5,562) validated the original Mini-IPIP five-factor structure, and supported an extended six-factor model also indexing Honesty-Humility. The Mini-IPIP6 reliably predicted variation in hours spent performing activities relating to aspects of personality (e.g., socializing, voluntary/charitable work, housework, and computer games). The Mini-IPIP6 also differentially predicted criterion outcomes such as religious affiliation and identification, political orientation, beliefs about climate change, and willingness to make personal sacrifices for the environment. The 24-item Mini-IPIP6 (four items indexing each personality dimension) fills a niche where brief markers of the Big-Six dimensions of personality are desired. A regression equation demonstrating how to integrate parameters derived using representative New Zealand data with a given individual’s Mini-IPIP6 scores to estimate his or her predicted value for each criterion outcome is provided (e.g., predicted housework in a given week), along with a copy of the scale itself, coding instructions and norms. This study represents the most detailed validation of a reliable and comprehensive broad-bandwidth public domain personality inventory for use in New Zealand to date.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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