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Record W1900177705 · doi:10.22230/src.2014v5n2a158

Academic Prototyping as a Method of Knowledge Production: The Case of the Dynamic Table of Contexts

2014· article· en· W1900177705 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.

Bibliographic record

VenueScholarly and Research Communication · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicWikis in Education and Collaboration
Canadian institutionsMcGill UniversityMount Royal UniversityMcMaster UniversityUniversity of British ColumbiaUniversity of GuelphUniversity of Alberta
Fundersnot available
KeywordsTable (database)Computer scienceFocus (optics)Process (computing)Production (economics)Rapid prototypingEthnographyKnowledge managementEngineering ethicsSociologySoftware engineeringEngineeringProgramming languageDatabase

Abstract

fetched live from OpenAlex

Academic prototyping, like ethnography or bench studies, is a way of producing new knowledge about an idea. It is a phase in a critical process. In fact, it is perhaps better to speak of academic prototyping, rather than of academic prototypes. In this paper, as an example, we discuss the Dynamic Table of Contexts, an academic prototyping project that has served for many years as a focus of ideas about what it means to remediate and improve on a venerable print tradition.

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)0.016
metaresearch head score (Gemma)0.008
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.293
Threshold uncertainty score0.907

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.074
GPT teacher head0.490
Teacher spread0.416 · 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