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Record W7006262516

Traces: Here/Not Here

2020· dissertation· en· W7006262516 on OpenAlexaff

Bibliographic record

VenueOCAD University Open Research Repository (OCAD University) · 2020
Typedissertation
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsOntario College of Art and Design
Fundersnot available
KeywordsIndexicalityReflexivityPosthumanPosthumanismPoint (geometry)Human bodyInterconnectivityPride
DOInot available

Abstract

fetched live from OpenAlex

Traces: Here/Not Here endeavors to put a positive spin on our mortality. We are here, and at some point we will no longer be here: by virtue of living, we will die - but what do we do with this time we have? This body of research creation is about life; about our time-limited lifetimes, our experience of it, and about the effects of our actions. It is about the affect of our interconnectivity with each other, human and non-human, animate and inanimate. By way of interactive artworks featuring playful and dynamic sculptures which must be activated by the physical effort of the artist, a collaborator or a visitor/participant, a durational performance is experienced leaving indexical marks, prompting mindful consideration of our inter-connectedness, and injecting optimism that we can use this opportunity to act for what matters most to each one of us. \nThrough a reflexive practice-led methodology, augmented by literature reviews of theorists, critical thinkers, artists, and art historians, the research investigates the themes of time, Posthuman interconnectedness, as well as investigating participatory and ludic art, which activates the body and the special knowledge creation centered there.

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)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.191
Threshold uncertainty score0.640

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0070.006
Scholarly communication0.0110.016
Open science0.0010.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.1910.070

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 head0.061
GPT teacher head0.296
Teacher spread0.236 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2020
Admission routes1
Has abstractyes

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