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
Abstract The idea of intelligence and intellectual abilities underlying human behavior is neither new nor limited to the Western world. However, this elusive construct has received considerable attention in the last 100 years, particularly from psychologists but also from other disciplines and fields ranging from behavior genetics and cultural anthropology to education and business. Intelligence is essentially a “latent” trait describing a complex set of human characteristics that psychologists and others contend is useful in describing individual differences across many of human behaviors ranging from skill in solving mathematics problems to success in the workplace. Measuring such an abstract construct is a demanding task and draws from theory, research evidence, and professional practice needs. Furthermore, fully understanding intelligence necessitates a multidisciplinary perspective drawing from all fields in the social and biological sciences, and a mixed methods approach to researching intelligence, including longitudinal and cross‐sectional, and correlational and experimental strategies.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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