Making a Living: The Gringo Ethnographer as Pimp of the Suffering in the Late Capitalist Night
Bibliographic record
Abstract
Set in the criminalized, racialized, and sexualized streets of Salvador da Bahia, this article presents experimental ethnographic glimpses of the deeply transnational aspects of desire, suffering, and violence in the disintegrating public spaces of a Northeastern Brazilian city famous for its global tourism fuelled by transnational desire for and consumption of Afro-Brazilian culture and bodies. The author reflects on the possibility of critical engagement between academic ethnographers from the North and the sex workers, street kids, crack users, and other marginalized social actors who make a living in the street. Refraining from facile, depoliticized celebrations of grassroots “critical” anthropology and other fantasies about empowering the subaltern, the author depicts the terror-as-usual at Bahian-street livelihoods from the necessarily exploitative position of a gringo ethnographer who is also making a living and a career from writing about the suffering of others. While this article, like all of Veissière’s work, is ultimately committed to a search for postcolonial social justice and critical dialogues between intellectuals and the subaltern, it also contemplates the horror of being an academic pimp who sustains a livelihood from exploiting human suffering and violence.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.023 | 0.024 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".