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Record W4392624859 · doi:10.1177/0308518x241233907

Jakarta: Taking the field seriously

2024· article· en· W4392624859 on OpenAlexaff
Emma Colven, Samuel Nowak, Dimitar Anguelov, Dian Tri Irawaty, Eric Sheppard, Helga Leitner

Bibliographic record

VenueEnvironment and Planning A Economy and Space · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in Asia
Canadian institutionsUniversity of British Columbia
FundersDivision of Social and Economic Sciences
KeywordsField (mathematics)Mathematics

Abstract

fetched live from OpenAlex

We respond as the Jakarta Collective to Prathiwi Putri’s constructive critique of Leitner and Sheppard’s research on Jakarta’s kampungs, to make visible the broader cluster of scholarship surrounding their research. Deploying six binaries, postcolonialism versus neoliberalism, non-capitalism versus capitalism, agency versus structure, displacement versus dispossession, and individual versus collective action, Putri suggests that Leitner and Sheppard stress the former while neglecting the latter. By taking the field seriously, we argue that the research of the Collective approaches these dialectically, teasing out their complex interrelations. Changes in Jakarta’s kampungs reflect its hybrid more-than-capitalist political economy, at the intersection of US and Chinese influence. The displacement of kampungs and kampung residents’ practices subsidize capitalism but they also contest its norms. Residents’ agency is significant; some gain but others lose, they act individually but also collectively. Highlighting more-than-capitalist practices opens up possibilities for alternative futures rather than simply documenting capitalist hegemony.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.046
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0200.018
Scholarly communication0.0170.012
Open science0.0010.008
Research integrity0.0050.010
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.015
GPT teacher head0.264
Teacher spread0.249 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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