Robbie Peters. <i>Surabaya, 1945–2010: Neighbourhood, State and Economy in Indonesia’s City of Struggle</i>. Singapore: NUS Press, 2013, 272 p.
Bibliographic record
Abstract
Before moving to Jakarta, I lived in Surabaya as a student from 1982 to 1990.The Surabaya of then was just beginning to represent itself as a world class city with the new landmarks of Tunjungan Plaza and later Delta Plaza, forming a belt of international hotels, offices, and shopping malls around kampung neighborhoods.Little did I realize that the city then was undergoing a major transformation marked by a shift from a city of work to a space of consumption.Robbie Peters came to Surabaya almost a decade later but at a most critical time in the history of the city during the fateful year of 1998.He thus understood especially well how the aftermath of 1998 (and what came before) had triggered a series of unprecedented crises in the forms of ninja, terrorism, and urban renewals all of which have profoundly shaped the neighborhood of Dinoyo-the subject of his study., 1945-2010 focuses on a kampung where people live a life at the margins of center of the city across different socio-political fields of postcolonial Indonesia.This neighborhood is specific in its proximity to factories and later shopping malls which took advantage of their labor, but the people in the kampung are more informal workers than proletariats.This set the stage for Peters to show the uneven relations between the kampung and the city as a kind of tension-filled duality that represents the larger relation between people and the state.Sometimes it appears we are being offered a choice between seeing Dinoyo surrender to the bureaucratic rationality of the state or stay with their kampung ethos of solidarity.The choice seems clear when outside in the street lurks the world of state power and capitalist modernization. SurabayaConsistent with the interest of anthropologists, Peters shows how Dinoyo kampung is given substance of neighborliness through the practices of slametan (feast-giving) to observe important events that happen in one's life such as death, marriage, and birth, which at once constitute a sense of solidarity and community.Peters however, does not regard kampung as inherently coherent or harmonious, indeed he believes its formation to be an outgrowth of control and crisis, territoriality and domination against which slametan continues to be enacted.This kind of formulation allows politics (rather than culture) to play a significant part in the book.Surabaya,
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".