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Record W4409676758 · doi:10.31235/osf.io/pq7p2_v1

Bantar Gebang: An Urban-Refuse Waste Picker Community at Indonesia's Largest Landfill

2017· preprint· en· W4409676758 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

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicWaste Management and Recycling
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsWaste managementMunicipal solid wasteEnvironmental scienceBusinessEnvironmental planningEngineering

Abstract

fetched live from OpenAlex

This paper discusses Bantar Gebang, a landfill site twenty miles east of Southeast Asia's largest city Jakarta, Indonesia and considers the landfill as an extension of Jakarta's urban residential space. The discussion includes geography and political economy of the landfill and of Indonesia, as well as the lives of Indonesian Waste Pickers, and other related communities. Documentary films about Global waste picker communities as well as political organization among these communities are analyzed.Keywords:Waste, Indonesia, Landfills, Trash, RefusePlease cite as:Oman-Reagan, Michael P. 2012. “Bantar Gebang: An Urban-Refuse Waste Picker Community at Indonesia's Largest Landfill.” SocArXiv, Open Science Framework. Manuscript, submitted January 23, 2017. osf.io/preprints/socarxiv/pq7p2

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 categoriesMeta-epidemiology (narrow), Open science, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.243
Threshold uncertainty score1.000

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 science0.0020.009
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.037
GPT teacher head0.265
Teacher spread0.228 · 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

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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