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Record W6925364485 · doi:10.17613/myzx7-mfz41

The Daughters of Metis

2012· article· en· W6925364485 on OpenAlexaboutno aff

Bibliographic record

VenueKnowledge Commons (Lakehead University) · 2012
Typearticle
Languageen
FieldEngineering
TopicConstruction Management and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsDominionMetisPower (physics)Identity (music)DialecticNarrativeMaximGreeks

Abstract

fetched live from OpenAlex

By attending closely to three ancient stories concerned with the origin and effect of patriarchal dominion, this essay seeks at once to discern the tragic dialectic according to which patriarchal authority operates and to open new possibilities for politics beyond the logic of domination and force. The stories of Zeus's consumption of Métis in the Theogony, of Agamemnon's sacrifice of Iphigeneia in the Agamemnon and of Athena's attempt to establish a just human community in the Eumenides articulate something of the logic of force that underlies and undermines patriarchal dominion at its very origins. These stories also, however, suggest another possibility for politics insofar as they give voice to the transformative political intelligence known to the Greeks as metis. This habit of thinking is dynamic and open in such a way that it can actualize what Hannah Arendt has designated as genuine political power: the ability to bring words and deeds together to cultivate relations and create new realities. The power of metis, it is suggested, is a habit of thinking capable of weaving difference into community with an eye toward justice. This essay turns to these ancient stories in order to draw out the possibilities metis holds for a new politics in the face of the chronic, pathological failures of the logic of force that has historically animated patriarchal politics.

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)0.001
metaresearch head score (Gemma)0.002
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: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0080.007
Scholarly communication0.0040.003
Open science0.0000.005
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0090.002

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 head0.207
Teacher spread0.193 · 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
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
Published2012
Admission routes1
Has abstractyes

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