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Record W7040876179

Long Shadows Cast

2024· other· en· W7040876179 on OpenAlexaboutno aff

Bibliographic record

VenueLancaster EPrints (Lancaster University) · 2024
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsGlacial periodShadow (psychology)GlacierThe ImaginaryPremiseIdeal (ethics)Shot (pellet)Quarter (Canadian coin)Symbol (formal)Indigenous
DOInot available

Abstract

fetched live from OpenAlex

Long Shadow Cast is a series of 9 glass watch faces ( 5cm diameter) painted with glacial flour ( sediment left by retreating glaciers ). Each drawing depicts (post) glacial site in Switzerland visited by the artist in summer 2023 through her residency at Musee d’art du Valais where she also gathered glacial flour left by retreating glacier used here as the pigment to make the images. Placed on an OHP, shadows are cast on the wall. The viewer sees not the drawing but its trace, via the means of this nearly obsolete technology. The yellow glow from the electric bulb of lends the work a sepia glow, recalling early photographic images of high mountain areas before the impact of that industrialisation of that period was to be seen. The work explores ideas of permanence, critiquing associations of the drawn mark as a fixed entity. Here , a mark made in shadow is a mark contingent on its environment (lighting conditions) to take shape. The premise reflects Jean Luc-Nancy's observation ( 2011) that a drawing is in a state of becoming. This theory of drawing has a critcial relationship to the depicted glacial environments. What appears to be fixed and timeless in in the drawing, is revealed as shifting and fluid in its shadow. The work also enters into critique of the romanticized view of high mountain areas as remote, out of reach and uninhabited, and as an imaginary sublime. In fact, this is an impossible ideal for these mountains are places of passage, pilgrimage and leisure pursuits and resources used by humans for centuries to support their lives, an idealised space as impossible to inhabit as a shadow. The work is part of the wider project Emergency! about what emerges as a result of glacial retreat. Exhibited at John Muir Trust 2024.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.418
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0510.468

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 head0.019
GPT teacher head0.224
Teacher spread0.205 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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