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Record W2994801036 · doi:10.28968/cftt.v5i2.29619

Neurological Disturbances and Time Travel

2019· article· en· W2994801036 on OpenAlexaff
Denielle Elliott

Bibliographic record

VenueCatalyst Feminism Theory Technoscience · 2019
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsYork University
Fundersnot available
KeywordsMemoirTemporalityEthnographyAphasiaAestheticsPoliticsPsychologyPsychoanalysisSociologyCognitive psychologyEpistemologyLiteratureAnthropologyArtPhilosophy

Abstract

fetched live from OpenAlex

This paper, positioned at the intersection of anthropology, science and technology studies, and feminist affect theory, considers shifts in memory and neurological disturbances that accompany traumatic brain injuries. Anomia, or anomic aphasia, is the inability to recall certain words, names, or colors caused by damage to the parietal or temporal lobes in the brain. Anomia is a disorder ‘on the verge’ – there but not quite, a forgotten memory, reluctant to be conjured. How might experimental ethnographic memoir help us uncover such forgotten memories and make sense of neurological disturbances pathologized by science and medicine? My account contributes to a growing body of literature that uses ethnographic memoir as political critique, blending the personal and theoretical, situating the intimate within larger historical and social contexts. It suggests that ethnographic memoir, with attention to the affective interiority of memories, merged with theoretical analyses and political critiques of medicine and/or therapeutic interventions, offer new understandings of being and temporality.

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)0.000
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.007
Scholarly communication0.0030.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.014
GPT teacher head0.239
Teacher spread0.225 · 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

Citations7
Published2019
Admission routes1
Has abstractyes

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