Philippine Housing Takeover: How the urban poor claimed their right to shelter
Bibliographic record
Abstract
On 8 March 2017, the Philippine urban poor marched to Pandi, Bulacan calling for their right to housing. Dubbed “Occupy Bulacan” and led by KADAMAY, the takeover succeeded in occupying 5,300 socialized housing units in the area. Prior to the takeover, 15,000 public housing units in Bulacan were deteriorating from disuse while thousands of families were living as homeless or relegated to informal settlements. Citing difficulties in acquiring decent housing, together with the availability of idle houses, KADAMAY members were compelled to take matters into their own hands and staged a takeover. Despite disapproval from various entities, KADAMAY remained steadfast in its stance. One year later, the Philippine Congress signed a resolution prompting the state housing agency to award the housing units to qualified “occupiers.” This level of victory had never been reached since the “golden years” of the Philippine urban poor movement in the 1970s. Here I describe what is possibly the largest organized takeover of government-built housing in the global South, with an emphasis on the ensemble of tactics and strategies that KADAMAY employed. This consists of the “arouse, organize, mobilize” (AOM) strategy, a “repertoire of contention”, and a “repertoire of strategies”. I also contextualize the takeover within local and international economic and political conditions, situate KADAMAY’s place in the urban poor movement, and identify other factors that led to the takeover’s success.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.026 | 0.019 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".