Communal intimacy and the violence of politics: Understanding the war on drugs in Bagong Silang, Philippines By Steffen BoJensen, KarlHapal, Ithaca: Cornell University Press. 2022. 207 pages. $33.95 (paperback). ISBN: 9781501762772
Bibliographic record
Abstract
President Rodrigo Duterte's war on drugs from a non-Duterte centric perspective, focusing on how it was conducted in one particular place.In the Philippines, the 1991 Local Government Code created subnational levels of government, consisting of provinces, cities, municipalities, and(at the lowest level) barangays.Relying on ten years of fieldwork, Jensen and Hapal's book analyzes the war on drugs in Barangay Bagong Silang, an urban poor community of 250,000 people located at the northern limits of Caloocan City, Metro Manila's most northerly city.After his May 2016 election, intensifying during 2017 and continuing until his end of term in 2022, the Duterte presidency became internationally infamous for its war on drugs, a revanchist campaign taking the lives of up to 30,000 people overwhelmingly from the urban poor.Indeed, Winn (2019, p. 25) described the war on drugs as "among the bloodiest massacres in recent Southeast Asian history" and something "racking up a body count seldom seen outside large-scale land battles" (p.128)."This ongoing massacre," wrote Winn (2019, p. 129), came "to define the modern Philippines."Jensen and Hapal discuss how the displacement of the urban poor from other parts of Metro Manila to Bagong Silang produced an urban underclass of young men perceived to be magulo (disorderly) and in need of disiplina (discipline), which was provided by older men involved in | e1
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.015 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".