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Record W2300831740 · doi:10.1017/cbo9781316337875.008

Fighting Fair

2015· book-chapter· en· W2300831740 on OpenAlexaff
Allan C. Hutchinson

Bibliographic record

VenueCambridge University Press eBooks · 2015
Typebook-chapter
Languageen
FieldSocial Sciences
TopicTorture, Ethics, and Law
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsExpansiveAbandonment (legal)WarrantLawPolitical scienceLaw and economicsSociologyBusiness

Abstract

fetched live from OpenAlex

The debate within military and legal ethics about the nature and limits of the professional means used to achieve appropriate and just ends is part of a larger and more expansive moral debate around ‘fair play’. The primary quandary is over both whether the ends can ever justify the means and whether different ends warrant different means: If the end is so warranted and so just can it sanction the use of any means to achieve it? Or does the resort to unjust and extreme means go so far as to negate or invalidate the previous justness of the ends sought? These are pertinent and perennial challenges for both military officers and professional lawyers. Most would agree that, even if the ends to be pursued were entirely just and warranted, this does not give people carte blanche to achieve those ends by whatever means possible. This would be less an ethical stance and more an abandonment of one. ENDS AND MEANS The basic thrust of military ethics is that any and all violence in war must be justified: it counsels a minimalist approach. No matter how just or worthy the cause undertaken, the prosecution of a just war demands that only just methods be used – the moral defensibility of the ends do not justify the resort to any possible means to achieve them. Moreover, the ethical focus is on both the why and the how of military action. Intentions and consequences must be evaluated together. Bad motives can taint what would otherwise be a justified consequence. Indeed, on a more general scale, if warring parties engage in unjust means, this can seriously compromise the justness of the war being waged. Accordingly, violence that is not militarily necessary violates jus in bello , but not all violence deemed militarily necessary is morally permissible.

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 imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.029
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0090.041
Scholarly communication0.0120.015
Open science0.0020.009
Research integrity0.0080.011
Insufficient payload (model declined to judge)0.0290.005

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.

Opus teacher head0.078
GPT teacher head0.267
Teacher spread0.189 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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