Bibliographic record
Abstract
This book is a collection of essays in Indonesian history and archaeology dealing with different and multiple trajectories, along four broad themes. The first part of the book covers competing or evolving representations of events, customs or traditions, and historical personae in Indonesian official and popular expression, as they are shaped by economic, political, and cultural forces. The second part deals with memories of war and peace, examining transnational conflict and collaboration, the role of political elites and state projects dealing with the aftermath of military aggression, while also focusing on the impact and responses of civilians. The third part focuses on how state and civil societies frame historical figures, in ways that transcend the dichotomy of heroes and victims. The fourth part of the book looks at the way Indonesian museums and museology serve as sites where new kinds of memory work occur, in a post-1998 era. The book is designed with the aim of clearing a space for a plurality of memory works. Discussions in this volume extend from Loloda island in Eastern Indonesia, to Sabang island at the north westernmost end of the archipelago, and to the cosmopolitan centers. Temporally, it covers the colonial, the post-independence and contemporary eras. By juxtaposing diverse works, the book offers a new vista of multiple trajectories of memory being traced out in and about Indonesia. This is an open access book.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.016 |
| Scholarly communication | 0.015 | 0.018 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".