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Record W2170110627 · doi:10.2304/elea.2007.4.3.266

In Medias Res: Reading, Writing, and the Digital Artefact

2007· article· en· W2170110627 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

VenueE-Learning and Digital Media · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOptimal distinctiveness theoryReading (process)Variety (cybernetics)Computer scienceRelation (database)Human–computer interactionLiteracyHypermediaMultimediaPoint (geometry)RecreationWorld Wide WebLinguisticsSociologyPsychologyArtificial intelligencePedagogySocial psychologyPolitical science

Abstract

fetched live from OpenAlex

In information systems and end-user computer research, ‘using’ appears to encapsulate a range of activities, such as reading, writing, viewing and so on. And yet it is a grossly inadequate descriptor for any of these activities, failing to account for the fact that texts — digital or otherwise — are produced and engaged by humans for a variety of purposes, from study to recreation. The wide adoption of ‘use’ as a descriptor for engagement with hypermedia reflects the challenges inherent in understanding and facilitating interaction with complex multimedia artefacts. It also points to a potential problem with research in this area: do attempts to accommodate the complexity of the digital artefact by devising terms that synthesize the range of literacy processes involved in human—computer interaction deter us from attending to the distinctiveness of those processes? The author takes up this question by considering how notions of reading and writing have been construed in relation to digital media, and whether such notions are in fact useful in furthering understanding of digital literacy.

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)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.916
Threshold uncertainty score0.948

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.011
GPT teacher head0.278
Teacher spread0.268 · 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