Our bodies are our own: resistance to ABC-based HIV-prevention programmes in northern Tanzanian conservation organisations
Bibliographic record
Abstract
ABC-based HIV-prevention programmes have been widely employed in northern Tanzanian wildlife conservation settings in an attempt to (re)shape the sexual behaviours of conservation actors. Utilising findings from 66 semi-structured interviews conducted in 2009-2010, this paper examines ABC prevention as a form of Foucauldian governmentality--circulating technologies of power that mobilise disciplinary technologies and attempt to transform such efforts into technologies of the self--and explores how individuals understand and respond to attempts to govern their behaviour. ABC regimes attempt to rework subjectivity, positioning HIV-related behaviours within a risk-based neoliberal rationality. However, efforts to use ABC as a technology to govern populations and individual bodies are largely incommensurate with existing Tanzanian sociocultural formations, including economic and gendered inequalities, and local understandings of sexuality. The language research participants used to talk about ABC and the justifications they offered for non-compliance illuminate this discrepancy. Data reveal that the recipients of ABC campaigns are active producers of understandings that work for them in their lives, but may not produce the behavioural shifts envisioned by programme goals. These findings corroborate previous research, which questions the continued plausibility of ABC as a stand-alone HIV- prevention framework.
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".