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Record W2132262134 · doi:10.1017/s1537592708080468

Islands of Agreement: Managing Enduring Armed Rivalries

2008· article· en· W2132262134 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePerspectives on Politics · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Peace and Security Dynamics
Canadian institutionsThe King's University
Fundersnot available
KeywordsAssertionConflict resolutionAgreementNeglectInternational conflictArmed conflictPolitical scienceResolution (logic)PhenomenonConflict managementSociologyLawEpistemologyPoliticsPsychologyPhilosophyComputer science

Abstract

fetched live from OpenAlex

Islands of Agreement: Managing Enduring Armed Rivalries. By Gabriella Blum. Cambridge, MA: Harvard University Press, 2007. 355p. $49.95. Gabriella Blum's book is built on the assertion that some conflicts cannot be resolved. She argues that since some conflicts will always be inescapable, the academic approach should move away from conflict prevention and resolution to the broader and more accurate notion of conflict “management.” Blum argues that considering conflicts as one whole phenomenon, or as a total relationship, leads scholars to search for one big (and often simplistic) solution for their resolution. She maintains that interstate relations are multidimensional and that conflicts should be seen as only one aspect of interstate relations. She asserts that “by concentrating our efforts … on conflict resolution only, we often neglect the potential of reinforcing those elements that fall outside the conflict yet inside the relationship” (p. 5).

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.

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)0.000
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.714
Threshold uncertainty score0.430

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.022
GPT teacher head0.296
Teacher spread0.274 · 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