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Record W2931509134 · doi:10.1177/0308518x19840365

Strategizing the for-profit city: The state, developers, and urban production in Mega Manila

2019· article· en· W2931509134 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnvironment and Planning A Economy and Space · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in Asia
Canadian institutionsUniversity of Calgary
FundersUniversité Sorbonne Paris CitéNational University of Singapore
KeywordsReal estate developmentMetropolitan areaUrban planningReal estateBusinessAutonomyEconomic growthEconomic systemEconomicsPolitical scienceFinanceEngineeringCivil engineeringGeography

Abstract

fetched live from OpenAlex

This article explores the evolving role of real estate developers in the wider metropolitan region of Manila, the Philippines. We argue that, given the relational nature of these actors, they are a relevant object of analysis for the formulation of “mid-level” theories that take into account both global, macroeconomic trends and local, history-dependent contingencies. As we consider developers’ activities and interactions with a wide range of public and private actors, we retrace their gradual empowerment since the beginning of the postcolonial period. As a handful of powerful land-owning families created real estate development companies, urban production quickly became dominated by a strong oligarchy capable of steering urban development outside the realm of public decision-making. Philippine developers subsequently strengthened their capacity by stepping into infrastructure provision, seemingly expanding their autonomy further. More recently, however, we argue that while the role of private sector actors in shaping urban and regional trajectories has scaled up, their activities have been tethered more strongly to a state-sponsored vision of change. Both by reorienting public–private partnerships (PPP) toward its regional plans, and by initiating new forms of public–private partnerships that give it more control, the state is attempting to harness the activity of developers. We characterize this shift as a move from the “privatization of planning” to the “planning of privatization” of urban space.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.305
Threshold uncertainty score0.423

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.238
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it