MétaCan
Menu
Back to cohort
Record W4315647247 · doi:10.24140/ijsim.v6.n1.02

Media Archaeology Experiences: Method, Meaning and Amusement

2022· article· en· W4315647247 on OpenAlexaff
Rod Bantjes

Bibliographic record

VenueInternational Journal on Stereo & Immersive Media · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsMateriality (auditing)Value (mathematics)ScholarshipContext (archaeology)Tacit knowledgeMeaning (existential)Experiential learningEpistemologySociologyAestheticsRepresentation (politics)ArtHistoryComputer sciencePoliticsPhilosophyArchaeology

Abstract

fetched live from OpenAlex

In this paper I make four interventions in favour of the seductive value of experiential media archaeology. 1) The constellation of material artefacts that mediate between us and the world are an implicit context for historic writing on perception, representation and epistemology. Engagement with the materiality of these often forgotten artefacts offers insight into the meanings of texts that exclusively text-based scholarship would otherwise miss. 2) Tacit, artisanal knowledge embedded in artefacts sometimes exceeds that which can be found in written texts. I argue that an effective way of accessing this material logic is to re-build old artefacts to see how they work. Applying the theory of extended cognition to this process, I make a case for its unique epistemological value. 3) I show how the seductive intimacy of these objects can be amplified by re-imagining their aesthetic possibilities. 4) I discuss the educational value of the “rational recreation” with media artifacts as “philosophical toys.”

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.025
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.026
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.006
Science and technology studies0.0110.039
Scholarly communication0.0190.011
Open science0.0030.015
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0100.001

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 head0.040
GPT teacher head0.350
Teacher spread0.310 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations2
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal on Stereo & Immersive MediaSame topicDigital Games and MediaFrench-language works237,207