MétaCan
Menu
Back to cohort
Record W7028344026

Eternal youth and the myth of deconstruction an archetypal reading of Jacques Derrida and Judith Butler

2024· article· en· W7028344026 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotanical Research and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsDeconstruction (building)MythologyReading (process)Representation (politics)CLARITYStyle (visual arts)Close readingMeaning (existential)
DOInot available

Abstract

fetched live from OpenAlex

In Eternal Youth and the Myth of Deconstruction, Bret Alderman puts forth a compelling thesis: Deconstruction tells a mythic story. Through an attentive examination of multiple texts and literary works, he elucidates this story in psychological and philosophical terms.Deconstruction, the method of philosophical and literary analysis originated by Jacques Derrida, arises from what Carl Jung called "a kind of readiness to produce over and over again the same or similar mythical ideas." In the case of deconstruction, such ideas bear a striking resemblance to a figure that Jungian and Post-Jungian writers refer to as the puer aeternus or eternal youth. To make his case, in addition to a careful analysis of numerous Derridean texts, he offers readings of literary works by Milan Kundera, J.M. Barrie, Dante, Apuleius, and others. These texts help illustrate that deconstruction’s preoccupations over questions of presence, deferral, authority, limits, time, and representation are also recurrent issues for the eternal youth as described by Marie-Louise Von Franz and James Hillman. Judith Butler’s deconstruction of sex and gender reflects similar patterns, and she features in this work as a contemporary exemplar of the deconstructive approach.Eternal Youth and the Myth of Deconstruction will be a compelling read for both students and teachers of depth psychology and continental philosophy. The clarity of its style will be appealing to advanced scholars and educated laypersons alike

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.684
Threshold uncertainty score0.121

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 head0.025
GPT teacher head0.260
Teacher spread0.235 · 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 designOther design
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
Published2024
Admission routes1
Has abstractyes

Explore more

Same topicBotanical Research and ApplicationsFrench-language works237,207