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Record W3035838198 · doi:10.24908/iqurcp.14055

The Pieces We Leave Behind: A Tale of Two Artists and a Desk

2020· article· en· W3035838198 on OpenAlexvenueaboutno aff
Hannah Mostert

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsnot available
Fundersnot available
KeywordsDeskPossession (linguistics)PaintingNephew and nieceVisual artsObject (grammar)ArtArt historyHistorySociologyLawLinguisticsPhilosophyPolitical science

Abstract

fetched live from OpenAlex

How do objects gather value and bear the weight of history? This research project addresses this question through research into an old wooden desk stored in the corner of an office at Queen’s University. It has six drawers coloured with a black cherry stain and decorative wooden handles. Adhered onto the desktop surface is a thin overlay of dark leather, to which is affixed a brass plaque that reads, "This desk was used by two famous Canadian artists, J.W. Beatty (1869-1941) and A.Y. Jackson (1882-1974). It was presented to Queen's University in 1980 by Dr. Naomi Jackson Groves, niece of A.Y. Jackson." J.W. Beatty and A.Y. Jackson were influential Canadian painters, whose stylistic focus on Canadian landscapes underpinned the formation of the Group of Seven; the desk was a non-sentient observer of their contributions to Canadian art and art history until 1968, when the desk left Jackson’s possession. Beyond the desk's immediate story, there is a larger research question: "how does the social biography of an object reveal the dynamics of its meaning, affect its value as a physical object, increase its significance in the art world, and determine where it is best preserved?" Using information uncovered during the summer of 2019, this presentation will reveal the importance of the desk’s provenance in relation to the stories of two influential Canadian artists, as well as share the process of investigating the biography of the desk through archival research methods.

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)0.004
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.059
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0520.034
Scholarly communication0.0200.011
Open science0.0030.011
Research integrity0.0040.010
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 head0.287
GPT teacher head0.355
Teacher spread0.068 · 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
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
Published2020
Admission routes2
Has abstractyes

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Same venueInquiry Queen s Undergraduate Research Conference ProceedingsSame topicCultural Heritage Management and PreservationFrench-language works237,207