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Record W2515847972 · doi:10.1111/edth.12184

Programming the Gesture of Writing: On the Algorithmic Paratexts of the Digital

2016· article· en· W2515847972 on OpenAlex

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

VenueEducational Theory · 2016
Typearticle
Languageen
FieldComputer Science
TopicDigital Media and Philosophy
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsHandwritingReading (process)Scripting languageComputer scienceGestureLinguisticsMultimediaProgramming languageArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract In the wake of the digital, some have recommended that we abandon the tedium of teaching handwriting to children in service of promoting “more creative” digital literacies. Others worry that an early diet of keyboard and screen may have deleterious effects on children's social, emotional, and cognitive development, as well as their physical well‐being. Yet in this debate, the algorithmic scripts and digital surfaces underwriting these new reading, writing, and mathematical practices are, with a few notable exceptions, almost exclusively ignored. In this essay, Catherine Adams asks whether the digital, and the reading and writing spaces it affords, are of consequence to our habits of thinking and ways of being, particularly in light of the possible obsolescence of pen and paper in schools. She shows that writing using a word processor is no mere mechanical pressing of keys, but an intricate ballet of writerly reading eyes and readerly writing hands, caught up in a dynamic environment of algorithmic paratexts and copy‐cut‐paste thinking.

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)0.000
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score0.189

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 science0.0010.000
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 head0.014
GPT teacher head0.236
Teacher spread0.222 · 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