Capitalist pigs: Governmentality, subjectivities, and the regulation of pig farming in colonial Hong Kong, 1950–1970
Bibliographic record
Abstract
This paper analyses the philanthropic governmentality of the Hong Kong colonial government during the Farm Improvement Program (1950–70), focusing on the utilization of pigs, interest-free loans, and the spatial constitution of pig farming as technologies to transform refugee farmers into ‘productive workers’. This research has three primary objectives: to (1) elucidate how the production of knowledge and governing technologies, including the spatial design of livestock production, facilitated the disciplining of pig farmers in a colonial context; (2) expand Foucauldian governmentality analysis into the realm of the regulatory mechanisms of food production systems by documenting how philanthropic pig donations, lending programmes, and the distribution of material benefits promoted capitalist pig production; and (3) demonstrate how technologies – specifically the social construction of pigs and the spatial constitution of pig farming practices – moulded the subjectivities of colonial pig farmers. Empirical analysis is based on archival research and in-depth interviews with 19 pig farmers and two pig farmers’ association leaders. We identify the provision of free pigs and pigsties, the demonstration of new spatial pig-raising practices, and the establishment of interest-free lending systems as the major technologies of governance employed under the Farm Improvement Program. Through these technologies refugee farmers from mainland China learned and internalized concepts of efficiency, productivity, farm management, and self-help. The technologies of the Farm Improvement Program were not just philanthropic activities, they were political tactics to confront the penetration of communism into the colony by changing the practices, productivity, and subjectivities of refugee farmers.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.002 | 0.001 |
| 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".