Globalization and modernization: an obesogenic combination
Bibliographic record
Abstract
Animal research has well established that a link exists between variations in corticosteroids and the proneness to excess body fat accumulation. Accordingly, it is known that adrenalectomy is an efficient approach to counteract weight gain in most animal models of obesity. In humans, the association between variations in corticosteroids, its stress-related environmental effects and the predisposition to obesity is more difficult to demonstrate. In this paper, we propose that this relationship is accentuated by globalization and modernization which favour a labour context imposing additional stress and changes in life habits promoting a positive energy balance. Our main hypothesis is that the increase in knowledge-based work, and the decrease of quality and duration of sleep both induce an increase in cortisolaemia and glycaemia instability, which results in an increase in food intake, a reduction in energy expenditure and body fat gain. The authors of this paper believe that, from a socioeconomic perspective, globalization leads every nation of the world in conflict with itself and may consequently represent a real problem. On one hand, there are preoccupations related to productivity and money making. On the other hand, people have to adopt a daily lifestyle leading to hyperphagia and decreased energy expenditure in order to maintain their economic competitiveness.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".