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Record W272099124 · doi:10.22329/wyaj.v25i2.4616

Figuring Reconciliation: Dancing With the Enemy

2007· article· en· W272099124 on OpenAlexvenueno aff
Jane Sutton, Nkanyiso Mpofu

Bibliographic record

VenueWindsor Yearbook of Access to Justice · 2007
Typearticle
Languageen
FieldArts and Humanities
TopicRhetoric and Communication Studies
Canadian institutionsnot available
Fundersnot available
KeywordsArgument (complex analysis)RhetoricDancePoliticsAestheticsSociologyLiteratureLawHistoryArtPolitical sciencePhilosophyLinguistics

Abstract

fetched live from OpenAlex

This essay is about figuring “argument as dance” and one way of conceiving how to live or embody argument as such. Concretely, it displays “argument as war” alongside a road in Mississippi after a white man shoots down James Meredith as he asserts his legal right to vote. And it tells “how to” perceive the shooting as dance by turning firstly to the performance of dance figured in the beginnings of rhetoric and then secondly, setting forth demystified methods and strategies of body-speech figuring argument as dance, rather than as war, through performances of Nelson Mandela. More generally, it explores a new meaning or experience of rhetoric by explicitly conjoining two historical times, two geographies, two speakers, enemies and dancers, that are inextricably interconnected. Using a combination of description and analysis, the first is a full display of three photographs picturing argument as war. The whole picture serves as a descriptive compass or guide for making our way analytically through argument as war and into dance language and behavior and their interconnections to argument. The second is a retrospective discussion of the background, dancing/argumentative practices, what is called “blinking on the behalf of the enemy,” of Nelson Mandela. Overall, the strategy of reticulating political times, chronology and political spaces, geography on the one hand, and argument as war and argument as dance on the other hand is to reconcile conflicting measures and to produce a performance practice (of rhetoric) of which there is no canon.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.864
Threshold uncertainty score0.307

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 studies0.0000.000
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 head0.084
GPT teacher head0.296
Teacher spread0.212 · 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
Published2007
Admission routes1
Has abstractyes

Explore more

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