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Record W4321462813 · doi:10.7202/1096061ar

Night Drawing

2023· article· en· W4321462813 on OpenAlexvenueno aff
Chantal Meng

Bibliographic record

VenueEthnologies · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicImpact of Light on Environment and Health
Canadian institutionsnot available
Fundersnot available
KeywordsLight pollutionArtificial lightEmbodied cognitionContext (archaeology)PerceptionAction (physics)Variety (cybernetics)Electric lightAestheticsVisual artsSociologyHistoryPsychologyArtComputer scienceArtificial intelligenceEngineeringArchaeologyOptics

Abstract

fetched live from OpenAlex

Night Drawing is an action that challenges perceptual habits—an embodied experience at the limits of the visible. Dealing with light at night is an urgent issue for a variety of social and cultural reasons and concerns the wider context of anthropogenic climate change. This paper deals with lighting conditions in the urban night on one hand and forms of cognition through drawing on the other. When it comes to artificial light at night, the foremost concerns include safety, light pollution, and the loss of darkness. However, the fact that darkness is also caused by and understood through artificial light is rarely discussed. Night Drawing aims to renegotiate long-standing assumptions about the benefits of urban nighttime lighting. This approach offers a challenge to the brighter the better idea and re-writes the appearance of nocturnal land/cityscapes. Night Drawing is a critical, innovative approach, a practice as a method to pay further attention to the representational power of the light at night. It aims at a technique of seeing in a new way—a re-examination and a new conception of urban darkness.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.116
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.016

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 head0.032
GPT teacher head0.291
Teacher spread0.259 · 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 designObservational
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

Citations1
Published2023
Admission routes1
Has abstractyes

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