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Record W1578445511 · doi:10.26530/oapen_411390

At the edges of states; Dynamics of state formation in the Indonesian borderlands

2012· book· en· W1578445511 on OpenAlexaboutno aff
Michael Eilenberg

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicAsian Studies and History
Canadian institutionsnot available
FundersLembaga Ilmu Pengetahuan IndonesiaRådet for Udviklingsforskning
KeywordsIndonesianDynamics (music)State (computer science)GeographyEconomic geographyPolitical sciencePhysicsComputer sciencePhilosophyLinguistics

Abstract

fetched live from OpenAlex

Cross border communitiesIn At the edges of states, Michael Eilenberg off ers a tantalizing contribution to the fi eld of borderlands studies, which he argues, center on the idea that the study of borderlands is critical to state formation.Thus, in the examination of the cross border Iban community stretched along the borderlands of Kalimantan and Sarawak on the Indonesian-Malay state border on the island of Borneo he has two stated goals.The fi rst goal is to situate state formation at the borderlands in a historical context.The second is to demonstrate process of local agency at the borderlands.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.009
Scholarly communication0.0080.005
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.015
GPT teacher head0.259
Teacher spread0.244 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations51
Published2012
Admission routes1
Has abstractyes

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Same topicAsian Studies and HistoryFrench-language works237,207