Bibliographic record
Abstract
The forces of ISIS (the so-called Islamic State) have lost most of the territory they held in Syria and Iraq, and the anti-ISIS forces are inclined to declare victory. On the presumption that we are in a context of aftermath to this struggle, that aftermath will itself be characterized by serious difficulties. A crucial problem in this context is that of returning foreign fighters. It is estimated that some 5600 persons left western countries to join the ISIS forces. Many of these men and women have been killed or imprisoned. Some will remain abroad to continue violent activities in alliance with ISIS or other jihadist forces. And some will seek to return home to the country they left. Regarding these people, referred to here as returnees, important issues of ethics and policy arise. These issues are likely to be disturbing and polarizing, with the result that some governments hold back from discussing them. Thinking that dodging the issues is a mistake, we explore some of them here, first setting the context in which they arise and then describing the central ethical dilemmas, which the tension between efforts to protect public safety and concern for the rights of suspected persons.
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 | 0.026 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.027 | 0.039 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.023 | 0.014 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".