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Record W2041323609 · doi:10.1177/1527476410385478

Subjectivity Through Self-Education

2010· article· en· W2041323609 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

VenueTelevision & New Media · 2010
Typearticle
Languageen
FieldArts and Humanities
TopicMuseums and Cultural Heritage
Canadian institutionsCarleton University
FundersSmithsonian Institution
KeywordsInteractive kioskVisitor patternSubjectivitySubject (documents)Digital mediaSociologyPresentation (obstetrics)Media studiesMultimediaPublic relationsComputer sciencePolitical scienceWorld Wide WebEpistemology

Abstract

fetched live from OpenAlex

This article looks at the use of digital kiosks and multimedia and multisensory presentation within the Smithsonian Institution’s National Museum of the American Indian (NMAI) in Washington, D.C., to denaturalize assumptions about visitor and audience subject formation. Museums like the NMAI include numerous media technologies including multimedia presentations and digital kiosks as they vie for the attention of museum visitors. Proponents of digital kiosks in public spaces argue that they promote active engagement among visitors by encouraging “free-choice” learning, a process through which users make decisions about the content reviewed. This article argues that “free-choice” learning makes several assumptions regarding subject formation and that these assumptions constrain understanding of how media technologies shape meaning making potential in indigenous museums. It suggests that the existence of digital kiosks and multimedia presentations indicates disparate assumptions about visitor subjectivity and that these media are integral to the “techniques of the self” performed by the museum visitor as a multicultural citizen.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.756
Threshold uncertainty score0.982

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0190.001

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 head0.030
GPT teacher head0.252
Teacher spread0.221 · 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