Personality and American State Differences in Obesity Prevalence
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
The study was conducted to determine whether state obesity-prevalence rates can be predicted by state differences in residents' levels on the Big Five personality variables (O. P. John & S. Srivastava, 1999). State obesity prevalence was the mean percentage of the state population from 2000 to 2005 with a body mass index > or = 30.0 as assessed by the Behavioral Risk Factor Surveillance System (Centers for Disease Control and Prevention, 2010), which currently interviews more than 350,000 adults annually. State neuroticism, extraversion, agreeableness, conscientiousness, and openness z scores, based on the responses of 619,397 residents to an Internet survey from 1999 to 2005, were taken from P. J. Rentfrow, S. D. Gosling, and J. Potter (2008). Alaska, Hawaii, and North Dakota had scores outside -3 and +3 standard deviations on at least 1 variable and were excluded as outliers. For the 47 remaining states, state obesity prevalence was significantly correlated with neuroticism (.35), agreeableness (.38), openness (-.44), socioeconomic status (-.74), white percentage (-.34), and urbanization (-.43). Multiple regression analysis showed that socioeconomic status could account for 54.0% of the criterion variance and that agreeableness, neuroticism, and openness together could account for another 17.1%.
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 | 0.002 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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