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Record W1505604732 · doi:10.22230/cjc.2015v40n2a2810

“Keeping up” through Teaching and Learning Media Software: “Introducing” Photoshop

2015· article· en· W1505604732 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.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Communication · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Education and Learning Practices
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMediationNegotiationMultimediaSet (abstract data type)InstitutionWork (physics)SoftwareDigital mediaKey (lock)PedagogyPsychologySociologyComputer scienceEngineeringWorld Wide WebSocial science

Abstract

fetched live from OpenAlex

Research on cultural industries suggests that the constant and rapid change to digital technologies used by creative practitioners requires that they continually upgrade their skills in order to remain relevant in their occupations. In this article, we present the results of an investigation into the mediation of Photoshop, focusing on how this digital imaging application software and its content are used to mediate access to cultural work. Teaching and learning Photoshop is presented as a key set of practices for digitally mediated cultural work, raising interesting paradoxes concerning Photoshop’s status as a digital imaging standard and how it is used by practitioners to negotiate access to occupations. The findings are drawn from two phases of an ongoing research project that includes interviews with practitioners in Canada and the United Kingdom and participant observation in a Greater Vancouver higher education institution.

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)0.007
metaresearch head score (Gemma)0.025
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.877
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.115
GPT teacher head0.389
Teacher spread0.274 · 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