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Record W2126856102 · doi:10.1002/meet.2014.14505101005

Mediating connections through materiality: Cultures and communities

2014· article· en· W2126856102 on OpenAlexaff
Ivette Bayo Urban, Lynne C. Howarth, Iulian Vamanu

Bibliographic record

VenueProceedings of the American Society for Information Science and Technology · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicMuseums and Cultural Heritage
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMateriality (auditing)Citizen journalismSociologySession (web analytics)Theme (computing)AestheticsIdentity (music)Computer scienceArtWorld Wide Web

Abstract

fetched live from OpenAlex

ABSTRACT Objects and their associations are a means of self‐expression and an integral part of identity making. Our panelists and our participants together will engage in exploring, defining and theorizing diverse research spaces of mediating connections through materiality. The panel is a discursive arena where participants embedded in different communities engage in material practices. In this session the panelists and participants will walk through the process of mediating connections through materiality in real time. The session is intended to be about the process—the means to an end, not an end in itself: shifting boundaries, identifying connections, moving margins and creating a participatory practice that embodies the very connections we hope to enact. Together we are moving from {apart from} to {a part of} – thus our practice reflects what we have experienced in our respective projects, facilitating in a material way the practice of boundary‐spanning. This interactive session essentially speaks to all aspects of the conference theme of Connecting Collections, Cultures, and Communities.

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)0.020
metaresearch head score (Gemma)0.030
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: none
Teacher disagreement score0.025
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.030
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.003
Science and technology studies0.0180.054
Scholarly communication0.0250.024
Open science0.0030.033
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 head0.022
GPT teacher head0.257
Teacher spread0.235 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the American Society for Information Science and TechnologySame topicMuseums and Cultural HeritageFrench-language works237,207