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Record W4384696045 · doi:10.22215/etd/2023-15606

Engaging Frozen Grounds: Practices of Spatial Imagination and Colonial Violence at the Canadian Arctic Coast

2023· dissertation· en· W4384696045 on OpenAlexaboutno aff
Stephanie Murray

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsTemporalitiesFutures contractColonialismRepresentation (politics)SociologyAestheticsNationalismTemporalityVisual artsHistoryEpistemologyArtPolitical sciencePoliticsArchaeologyLaw

Abstract

fetched live from OpenAlex

Recognizing drawing as a cornerstone of architectural representation, this research begins with the notion that a line doesn’t manifest as merely “the dot that went for a walk”. More than marks on a page, lines emerge as a thought pattern, a habit of engagement, or a physical act. Further, this research suggests that physical realities of the Canadian North, have not and can not be depicted by existing Western representational methods, thus limiting past, present and future spatial imagination. Through a series of research creation exercises and historical investigations, this research asks: What materialities and temporalities are articulated with drawing conventions, and how does this limit or erase spatial futures across the diversity of frozen landscapes? How can counter methods empower previously oppressed spatial possibilities and futures? How are these limitations related to Canadian settler nationalism? Can representational methods that transcend the colonial-dominant praxes of territorialization be accounted for?

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)0.007
metaresearch head score (Gemma)0.009
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 score0.071
Threshold uncertainty score0.514

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0430.061
Scholarly communication0.0140.004
Open science0.0030.009
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.038
GPT teacher head0.401
Teacher spread0.363 · 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
Published2023
Admission routes1
Has abstractyes

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