Bibliographic record
Abstract
Eighteen years after the first American drone strike, the US drone program now operates in a record-setting number of countries across the Middle East and Africa. This paper examines the Obama administration’s expansion of the US drone program through the lens of Ontological Security Theory, wherein states fulfill their need for security as a sense of being by engaging in uncertainty-reducing and identity-building international relationships, including dilemmatic conflicts. This paper argues that President Obama and his administration failed to adequately address the drone program’s domestic, constitutional, and international legal brokenness due to an ontological attachment to the morality behind the conduct of drone operations. In their public statements, administration officials rationalized the program as a medical tool eliminating “the cancerous tumor called an al Qaida terrorist” and presented drones as a morally superior alternative to the use of torture and of indefinite detention in Guantanamo Bay. As such, the Obama-era drone program existed both as an uncertainty reduction routine vis a vis the dilemmatic conflict of terrorism, as well as a reflexive, identity-building international relationship that established the program as a key element of the ‘forever war’ against al-Qaeda and set the stage for Trump-era program expansion. As this expansion proceeds, the program will only become further at odds with America’s long-term rational interests.
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 | 0.018 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.013 | 0.016 |
| Scholarly communication | 0.023 | 0.014 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.008 | 0.017 |
| Insufficient payload (model declined to judge) | 0.068 | 0.029 |
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".