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Record W2607405660 · doi:10.1017/s0010417517000044

The Price of Un/Freedom: Indonesia's Colonial and Contemporary Plantation Labor Regimes

2017· article· en· W2607405660 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

VenueComparative Studies in Society and History · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicAsian Studies and History
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsColonialismState (computer science)Palm oilLabor relationsWageWork (physics)Labor historyPolitical sciencePolitical economyEconomicsLabour economicsLaw

Abstract

fetched live from OpenAlex

Abstract Although often associated with colonial times, tropical plantations growing industrial crops such as rubber, sugar, and oil palm are once again expanding. They employ hundreds of thousands of workers, who still use remarkably basic tools. Flagging colonial continuities, labor activists campaign against the reemergence of unfree labor and “modern forms of slavery.” Paradoxically, labor activists also highlight the opposite problem: the casualization of plantation work, as workers are hired daily and fired at will. Recognizing that both “free” and unfree labor regimes have a long history in Indonesia, and plantations have pivoted between these modes more than once, my study compares plantation labor regimes in the colonial, New Order, and “reform” periods (post-1998) to answer three questions. First, given that employers always want to access disciplined labor at the lowest possible price, what were the conditions that led employers to rely on unfree labor in some cases, and “free” labor in others? Second, to what extent was unfreedom imposed as a response to excessive freedom among workers and peasants? Third, how were the costs of social reproduction distributed between workers and employers, and what pressures from workers or regulators (state, colonial, transnational) affected this distribution? In addition to published sources, I draw on my ethnographic research in West Kalimantan (2010–2015) to explore contemporary experiences of un/freedom among workers on state and private oil palm plantations.

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 categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.645
Threshold uncertainty score0.998

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 studies0.0030.009
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 head0.135
GPT teacher head0.376
Teacher spread0.240 · 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