Opening Up Openness: A Theoretical Sort Following Critical Incidents Methodology and a Meta-Analytic Investigation of the Trait Family Measures
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
Existing taxonomies of Openness's facet structure have produced widely divergent results, and there is limited comprehensive empirical evidence about how Openness-related scales on existing personality inventories align within the 5-factor framework. In Study 1, we used a critical incidents sorting methodology to identify 11 categories of Openness measures; in Study 2, we meta-analyzed the relationships of these categories with global markers of the Big Five traits (utilizing data from 106 samples with a total sample size of N = 35,886). Our results identified 4 true facets of Openness: aestheticism, openness to sensations, nontraditionalism, and introspection. Measures of these facets were unadulterated by variance from other Big Five traits. Many traits frequently conceptualized as facets of Openness (e.g., innovation/creativity, variety-seeking, and tolerance) emerged as trait compounds that, although related to Openness, are also dependent on other Big Five traits. We discuss how Openness should be conceptualized, measured, and studied in light of the empirically based, refined taxonomy emerging from this research.
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.
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 | 0.013 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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