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Record W2329496090

(re)imagining education as an un-coercive re-arrangement of desires

2016· article· en· W2329496090 on OpenAlexaffabout
Vanessa Andreotti

Bibliographic record

VenueOther Education · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicPhilosophy, Ethics, and Existentialism
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsArgument (complex analysis)NormativeOrder (exchange)PoetryLogos Bible SoftwarePerformativitySociologyEpistemologyAestheticsLinguisticsLiteraturePhilosophyArtTheology
DOInot available

Abstract

fetched live from OpenAlex

This text was first performed at the International Association for the Advancement of Curriculum Studies Conference in Ottawa on 29 May, 2015, where I took the liberty and the risk of deviating from the academic genre. However, I modified the text here in written form to adjust expectations to this form of communication. In this text, I use story telling, metaphors and poetry to introduce an argument that is not self-evident and does not produce a single normative claim for the way forward. The stories and metaphors I use come from different teachings, from multiple locations. What they have in common is their performativity: their potential to re-orient logos/logic in order to make room for the ineffable. In other words: instead of talking about an “un-coercive re-arrangement of desires” (Spivak, 2004, p. 526), the text invites you to live this possibility, for a moment...

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.049
Scholarly communication0.0080.010
Open science0.0010.003
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0030.001

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 head0.076
GPT teacher head0.325
Teacher spread0.249 · 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 designTheoretical or conceptual
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

Citations23
Published2016
Admission routes2
Has abstractyes

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