Of Fairies, Robots, Witches, and Zombies: Conceptualizing a History of Cross-Cultural Psychiatric Epidemiology in Nigeria
Bibliographic record
Abstract
Introduction The 1950s and 1960s were a time of significant promise for the development of psychiatric epidemiology around the world. While much of the nascent historiography has focused on the development of methods and projects in Europe and North America, it is also well recognized that the field had global ambitions during those decades. Through a number of international collaborative networks, preliminary efforts were made at developing methods for cross-cultural psychiatric epidemiology in a variety of non-Western contexts. This chapter will examine the historical development of psychiatric epidemiology in Africa, with particular emphasis on Nigeria and its relationship with two different projects: the Cornell-Aro project, which conducted a community study of symptoms of mental disorder in Yorubaland in 1961 to compare results with the famous Stirling County study in Canada, and the World Health Organization's International Pilot Study of Schizophrenia (IPSS), carried out from 1968–69, in which the same region served as a field research center contributing to the establishment of a methodology for the cross-cultural identification of a specific diagnostic entity. This chapter uses these two projects to make three broad arguments for the types of inquiries historians should be making in developing a global history of psychiatric epidemiology. First, this chapter argues that psychiatric epidemiology in Nigeria (and Africa more generally) has a multifarious history that complicates narratives of sources and origins at the same time that it recognizes the complex synergy between the “global” and “local” in the construction and dissemination of scientific knowledge. Second, in making the first argument it becomes clear that such a history must focus on the ways that conceptions of “culture” and cultural content are mobilized in service of the universal aspirations not only of these particular projects, but also psychiatric epidemiology more generally in postcolonial spaces. Third, this chapter demonstrates that a fruitful way to examine the mobilization of culture is through the tools of cross-cultural psychiatric epidemiology itself: namely the surveys and questionnaires that generate data about symptom prevalence and categorization. Neither the Cornell-Aro project nor the International Pilot Study of Schizophrenia were designed to produce definitive epidemiological data about mental illness in specific communities. They were established primarily as experiments in developing methodologies for psychiatric epidemiology that could be standardized and replicated in diverse cultural landscapes.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.013 | 0.072 |
| Scholarly communication | 0.012 | 0.015 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| 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".