Bibliographic record
Abstract
Indonesian historian Onghokham was “the best guide to Indonesia,” and he could be “the serious historian, the public intellectual, the sexual being, the quiet lover, or the hedonist and party host” (298). He was also “a maverick, an eccentric, an alcoholic, and an outsider who became an insider, [with] a mischievous wit” (295), as David Reeve writes in his biography of Onghokham—which is extraordinary for exposing virtually everything about Ong. As Ong said to his family, “I want the family to tell David everything bad about me,” which in some ways could include everything bad about the family as well (287). Ong died in 2007, too late to see the book, but Reeve, an Australian researcher with deep connections to Indonesia, has done a marvelous job of fulfilling Ong’s wish to tell the full story. Reeve coedited Onze Ong, a posthumous recollection by Ong’s friends, which was a key source for reconstructing Ong’s life; Reeve also relies on interviews and letters Ong wrote to his Cornell friends, such as Benedict Anderson, Daniel Lev, and Herbert Feith. The result is an affective narrative with a multiplicity of voices speaking to Ong’s emotional life, his identity, his worldview, and his lifestyle. We cannot help but admire Ong, who shows us how to remain oneself in the time and space within which one is embedded. As such, Ong’s biography is a critical intervention into the political establishment and cultural assumptions of Indonesian society.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.021 | 0.005 |
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".