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Record W2594111028 · doi:10.1386/vi.5.3.249_1

Walking together: Shared authority and co-mentorship between two artists on the move

2016· article· en· W2594111028 on OpenAlexaffabout
Kathleen Vaughan, Pohanna Pyne Feinberg

Bibliographic record

VenueVisual Inquiry · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicArtistic and Creative Research
Canadian institutionsConcordia University
Fundersnot available
KeywordsMentorshipNeighbourhood (mathematics)SociologyVisual artsCharismaMedia studiesArtPolitical scienceLaw

Abstract

fetched live from OpenAlex

Abstract We invite you to join us as we explore our co-mentorship through walking, artmaking and writing, all core aspects of our practices as artists. While meandering through the rich sensorial environment of Montreal’s waterside Parc-nature de l’Île-de-la-Visitation, our reactions to the surroundings played an influential role in shaping the character of this article. Our ideas emerged through the quiet heat of the early spring sunshine and amidst intermittent remarks about the birds flying by, the directionality of the flowing river, the strength of the wind, the sounds of lapping water, the families enjoying picnics, the demographics of the neighbourhood surrounding the park, and even the roar of a hydro dam we encountered for the first time. Drawing on a posthumanist framework, notions of shared authority borrowed from oral history, methods of call-and-response, and co-mentorship, the authors – a doctoral supervisor and a doctoral candidate in Art Education at Concordia University in Montreal – reflect on their hopes for and experiences of their work together as complementary, convergent, concurrent and symbiotic.

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)0.058
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 score0.037
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.058
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0370.040
Scholarly communication0.0260.007
Open science0.0040.024
Research integrity0.0040.009
Insufficient payload (model declined to judge)0.0110.002

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 head0.179
GPT teacher head0.402
Teacher spread0.223 · 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
Published2016
Admission routes2
Has abstractyes

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