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Record W7046992878

Echoing the Cicadas: Neo-Sophism, Gamification of Knowledge & the Expertise-Illusion in the Contemporary Infosphere

2023· other· en· W7046992878 on OpenAlexaff

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2023
Typeother
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsConcordia University
Fundersnot available
KeywordsDialecticAgency (philosophy)TextualityPower (physics)ConsciousnessEmbodied cognition
DOInot available

Abstract

fetched live from OpenAlex

For Plato, writing’s power for sophistry and its authority over the reader is founded on writing’s nature as incomplete without the embodied presence of the author, creating an asymmetrical reader-text relationship wherein the reader is active, and the text passive. The modern infosphere presents a new problem but at the same time connects back to this Platonic issue. The relationship between agency and patiency in Plato’s world of textuality is transformed by the mechanisms of the contemporary infosphere. Instead of silence, modern readers are confronted with a bombardment of voices competing for their attention. Conceived as a new tradition, the infosphere presents readers with an unbounded and ever-shifting horizon of texts and references as already interpreted answers. From this unbounded horizon—a product of what I call the collective memory paradox—the expertise-illusion arises within the consciousness of certain types of readers, when the dialectic between question and answer is dissolved through the isolating character of textuality, which is intensified by its form in the internet age. Genuine communication is corrupted when the reader’s agency is unknowingly replaced by the info-sophist’s agency. This is exemplified and amplified through various forms of the ‘gamification’ of knowledge, which encourages readers to seek compulsive accumulation of information, diverting them from thinking their own way to knowledge. This gamification can provide a false sense of agency, making readers think they ‘have’ knowledge, and thereby expertise. However, they have merely won the game of acquiring it within a framework that provisions them to do so.

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)0.006
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: Other · Consensus signal: Other
Teacher disagreement score0.011
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.039
Scholarly communication0.0110.014
Open science0.0010.006
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0050.001

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 head0.045
GPT teacher head0.295
Teacher spread0.250 · 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
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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