Searching for Conflict Related Missing Persons in Timor-Leste: Technical, Political and Cultural Considerations
Bibliographic record
Abstract
<span style="font-family: 'Times New Roman','serif'; font-size: 11pt; mso-fareast-font-family: Cambria; mso-ansi-language: EN-GB; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;" lang="EN-GB">This paper outlines the context in which many thousands of people went missing in Timor-Leste between 1975 and 1999. The issues related to estimating the exact number of missing are discussed, followed by a review of the mechanisms implemented by the government and civil society since independence to attempt to examine and investigate the fate of missing persons. The paper then examines the technical details involved with searching for the missing which impact on the effectiveness of the different mechanisms. Further complexities related to scientific and religious/cultural beliefs when dealing with the missing are discussed. The paper concludes with</span><span style="font-family: 'Times New Roman','serif'; font-size: 11pt; mso-fareast-font-family: Calibri; mso-ansi-language: EN-GB; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;" lang="EN-GB"> questioning the to date <em style="mso-bidi-font-style: normal;">ad hoc</em> approach to the search for the missing </span><span style="font-family: 'Times New Roman','serif'; font-size: 11pt; mso-fareast-font-family: Cambria; mso-ansi-language: EN-GB; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;" lang="EN-GB">in Timor-Leste, </span><span style="font-family: 'Times New Roman','serif'; font-size: 11pt; mso-fareast-font-family: Calibri; mso-ansi-language: EN-GB; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;" lang="EN-GB">and </span><span style="font-family: 'Times New Roman','serif'; font-size: 11pt; mso-fareast-font-family: Cambria; mso-ansi-language: EN-GB; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;" lang="EN-GB">providing suggestions for ways that the future search for the missing can realistically continue in light of other competing development priorities.</span>
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".