MétaCan
Menu
Back to cohort
Record W3041806129 · doi:10.18192/potentia.v10i0.4512

A Source of Our Strength

2019· article· en· W3041806129 on OpenAlexaffvenue
Nicholas Millot

Bibliographic record

VenuePotentia Journal of International Affairs · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicTorture, Ethics, and Law
Canadian institutionsCarleton University
Fundersnot available
KeywordsDroneTerrorismTortureMoralityAdministration (probate law)Political scienceLawElement (criminal law)SociologyPublic administrationHuman rights

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.808
Threshold uncertainty score0.644

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.014
GPT teacher head0.296
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes2
Has abstractyes

Explore more

Same venuePotentia Journal of International AffairsSame topicTorture, Ethics, and LawFrench-language works237,207