Modern Slavery Characterisation through the Analysis of Energy Replenishment
Bibliographic record
Abstract
The Brazilian economy was, until the end of the 19th Century, based on slave labour. However, in this first quarter of the 21st Century, the problem persists. These situations tend to be mistaken with “simple” violations of labour laws. This work aims to establish Occupational Health and Safety parameters, focusing on energy needs, to distinguish between the breach of labour legislation and modern rural slavery in the 21st Century in Brazil. In response to this challenge, bibliographical research was carried out on the feeding and energy replenishment conditions of Brazilian slaves in the 19th Century. Obtained data were compared with a sample where 392 cases of neo-slavery in Brazil are described. The energy spent and the energy supplied was calculated to identify the enslaved workers’ general feeding conditions in the two historical periods. The general conditions of food and water supply were analysed. It was possible to identify three comparable parameters: food quality, food quantity, and water supply. It was concluded that there is a parallelism of energy replenishment conditions between Brazilian slaves and neo-slaves of the 19th and 21st centuries, respectively, different from that of free workers. This difference can help authorities identify and punish instances of modern slavery.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".