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Record W2564156359 · doi:10.22230/src.2016v7n2/3a251

Re-Created Radio Dramas as Innovative Knowledge Environments

2016· article· en· W2564156359 on OpenAlexvenueno aff
John F. Barber

Bibliographic record

VenueScholarly and Research Communication · 2016
Typearticle
Languageen
FieldHealth Professions
TopicDigital Storytelling and Education
Canadian institutionsnot available
Fundersnot available
KeywordsActive listeningScholarshipOutreachContext (archaeology)Citizen journalismEphemeral keyCommunity radioSociologyMultimediaComputer sciencePolitical scienceWorld Wide WebMedia studies

Abstract

fetched live from OpenAlex

Background The author describes his efforts to re-create vintage radio dramas as participatory knowledge environments in which to explore both their context and original production, and to provide engaging listening opportunities for sound, the most ephemeral of all media.Analysis These efforts promote new knowledge environments for outreach, creative problem solving, rapid prototyping, and the social development of new literacies and skills.Conclusion and implications Because it is an intensely active experience, listening to sound and engaging directly with the imagination can promote direct listener involvement/engagement in a (re)new(ed) knowledge environment with increased opportunities for pedagogy and scholarship.

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.

How this classification was reachedexpand

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient 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 score0.801
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.002

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 head0.182
GPT teacher head0.493
Teacher spread0.311 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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