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Record W3111635295 · doi:10.7557/13.5489

Banlieue Nord: A Brief Contribution to How We Inhabit the North and How the North Inhabits Us

2020· article· en· W3111635295 on OpenAlexaffabout
Lena Gudd, Antonin Pons Braley

Bibliographic record

VenueNordlit · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsSituatedMythologyPower (physics)North westSpace (punctuation)GeographyRelation (database)SociologyEthnologyEnvironmental ethicsArchaeologyHistory

Abstract

fetched live from OpenAlex

Beyond its many simplified representations such as cold, hostile, uninhabited, or unknown, the north reveals itself as a complex and multiple space of interwoven geographical, cultural, social, and conceptual dimensions. Influenced by world views, the power of maps and myths as well as the very relation to the landscape itself as one of extraction or attraction, humans subjectively apprehend these multiple norths. By dwelling in the northern lands through experience or imagination, ‘southerners’ and ‘northerners’ alike do not simply inhabit the north; they are in turn inhabited by it. Situated at the ‘gates of the north’ in subarctic Canada, the mono-industrial company town Fermont fits its town centre entirely under a single roof. Planned and commissioned in the 1970s by a mining company, the town’s Utopian purpose was to ‘make a society’ in an inhospitable climate, while serving the exploitation of the mine. Fermont’s case serves here as a laboratory to understand the complexities of the north in more general terms. At the crossroads of image-based practices and the humanities, this contribution engages with the question of how humans inhabit the north and how they are inhabited by it.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.493
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.036
GPT teacher head0.243
Teacher spread0.206 · 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 teacher head, not a consensus.

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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