MétaCan
Menu
Back to cohort
Record W3121458012 · doi:10.22215/etd/2016-11438

North as Nature: An Ecocritacal Analysis of Royal Canadian Air Force Photography and Leslie Reid's Mapping Time

2016· dissertation· en· W3121458012 on OpenAlexaffabout
Hannah Keating

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicPolar Research and Ecology
Canadian institutionsCarleton University
Fundersnot available
KeywordsConstruct (python library)ArcticPaintingNarrativePhotographySemioticsLandscape paintingThe arcticVisual artsGeographySpace (punctuation)Art historyCartographyHistoryArtComputer scienceOceanographyEpistemologyLiteratureGeologyPhilosophy

Abstract

fetched live from OpenAlex

A semiotic analysis of visual narratives, this thesis explores representations of Arctic landscape to uncover discourses of North and Nature.In the mid-twentieth century, the Royal Canadian Air Force (RCAF) was tasked with photographing the Canadian Arctic to construct accurate maps of the region.And, following a residency with the Canadian Forces Artists Program in 2013, contemporary artist Leslie Reid began an ongoing series of paintings and photo-mosaics: Mapping Time.This trans historical thesis is dedicated to an ecologically sensitive approach and considers how aerial photographs of the RCAF not only represent space, but also construct narratives of Canadian sovereignty and contribute to an idea of North as Nature.Integrating examples of RCAF photographs into her photomontages, Reid asks viewers to contemplate the history of Arctic mapping and her paintings welcome a critical approach to representations of place, space, and landscape.

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)0.003
metaresearch head score (Gemma)0.006
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: none
Teacher disagreement score0.064
Threshold uncertainty score0.465

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.006
Science and technology studies0.0230.023
Scholarly communication0.0110.005
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.003
GPT teacher head0.230
Teacher spread0.227 · 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

Explore more

Same topicPolar Research and EcologyFrench-language works237,207