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Record W4213022685 · doi:10.1177/02632764221074182

Rethinking Human-Smartphone Interaction with Deleuze, Guattari, and Polanyi

2022· article· en· W4213022685 on OpenAlexaff
Nicholas Fazio

Bibliographic record

VenueTheory Culture & Society · 2022
Typearticle
Languageen
FieldNeuroscience
TopicEmbodied and Extended Cognition
Canadian institutionsYork University
Fundersnot available
KeywordsDeleuze and GuattariEpistemologyCognitive scienceCyberneticsPsychologySociologyPhilosophy

Abstract

fetched live from OpenAlex

An inbuilt theoretical deficiency of any cybernetic or phenomenological accounts of human-smartphone interaction is that their inherited frameworks suffer from lopsided explanatory proficiencies. Neither can explicate one ‘side’ of the interaction without inappropriately foisting those logics onto its dyadic counterpart. In this paper, both Michael Polanyi’s bio-philosophy and a Deleuzo-Guattarian philosophy of brain seek to remedy this conceptual deficit by positing a conceptual toolkit that incorporates pertinent cybernetic and phenomenological revelations while abjuring their dogmatizing propensities. This conjoined reading of Polanyi with Deleuze and Guattari asserts that temporary, bounded structures of interference between mind and machine – rooted in asymmetry, inertia, and labile planes of cognition – are the grounding dimension of human-smartphone interaction, which is itself taken as emblematic of our wider relations to smart technologies.

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)0.004
metaresearch head score (Gemma)0.006
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 score0.006
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.035
Scholarly communication0.0060.012
Open science0.0010.006
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.269
Teacher spread0.239 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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