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Record W4328053443 · doi:10.1386/eme_00150_1

Weakness exploitation: Predicting socially communicative devices as a successor to internet-based graphical user interfaces

2023· article· en· W4328053443 on OpenAlex
Jamy Li, Mark Chignell

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueExplorations in Media Ecology · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsUniversity of TorontoToronto Metropolitan University
Fundersnot available
KeywordsThe InternetSuccessor cardinalComputer sciencePoint (geometry)Graphical user interfaceHuman–computer interactionTransition (genetics)RobotInterface (matter)World Wide WebMultimediaArtificial intelligence

Abstract

fetched live from OpenAlex

Existing theories of technology transitions cannot predict what new technological paradigm will supplant the currently leading, internet-enabled graphical user interface paradigm. This article introduces a preliminary approach (‘weakness exploitation’) to explain the rise and fall of four technology ‘empires’: print, television, the internet and socially interactive devices (such as robots, chatbots and internet of things devices). The approach is related to technology diffusion and disruptive innovation, but with a predictive element induced from Marshall McLuhan’s descriptions of print and television as ‘extensions’ of the senses. It is applied to the internet as an historical example of a technology transition outside of McLuhan’s original analysis and to explain why excessive exposure to screen-rendered digital media as the internet’s exclusive access point may be replaced by a new ‘age’ of computationally intelligent, socially communicative devices. This new approach can help researchers and technologists conceptualize transitions between usage of incumbent and emerging 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.

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.271
Threshold uncertainty score0.820

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.052
GPT teacher head0.362
Teacher spread0.309 · 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