Bibliographic record
Abstract
In this article I explore how, in the League of Nations’ emerging anti-trafficking regime of the 1920s and 1930s, one category of race science — climate — played a prominent role in positing natural hierarchies between nations. My purpose is twofold: (1) to explain the currency of climate at this moment and to examine the trajectory of climate as an explanatory device in the intellectual history of ‘race’; and (2) to reflect on the biopolitical implications of explanations rooted in climate. The article begins with a description of how League of Nations delegates used climate as shorthand to refer to differences between the sexual mores of various nations. I then reflect more broadly on the emergence, submergence, and reemergence of climate in the history of race science, and its effects in practical settings. I move to a discussion of the significance of the age of consent as a category, and analyse the League of Nations-sponsored efforts to track ages of consent across countries as a biopolitical project. My overarching argument is that references to climate performed important ideological work in naturalizing hierarchical relations between nations. In arenas where diplomats sought to arrive at a consensus, such references rendered them more palatable and less disputable.
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.
How this classification was reachedexpand
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 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".