Integrating humans into pace-of-life studies: The Big Five personality traits and metabolic rate in young adults
Bibliographic record
Abstract
The pace-of-life syndrome (POLS) predicts that personality and metabolism should be correlated if they function as an integrated unit along a slow-fast continuum. Over the last decade, this conceptual framework has been tested in several empirical studies over a wide array of non-human animal taxa, across multiple personality traits and using standardized measures of metabolism. However, studies associating metabolic rate and personality in humans have been surprisingly scarce. Here, we tested whether there was covariation among personality scores, measured using the Big Five Inventory test, resting metabolic rate (RMR) and preferred walking speed (PWS) in a cohort of young human adults aged between 18 and 27 years old. We found a significant, negative relationship between RMR and Extraversion; less extraverted individuals had a 30% higher RMR than the most extraverted ones. No other personality traits correlated with RMR and none correlated with PWS. The negative correlation between Extraversion and RMR may suggest an allocation energy trade-off between personality and basal metabolism. Our results yielded equivocal support for the POLS and emphasized the need for more research on human to test the generality of this conceptual framework and further assess its validity.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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 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".