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Infrastructural Disruption, Entanglement and Change in Northern Manitoba

2025· article· en· W4416193755 on OpenAlexvenueaboutno aff
Philipp Budka

Bibliographic record

VenueAnthropologica · 2025
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
FundersUniversität WienEuropean Commission
KeywordsSubarctic climateArcticBayPort (circuit theory)TourismClimate changeIndigenousEthnography

Abstract

fetched live from OpenAlex

Situated at the junction of boreal forest, Subarctic tundra, and Hudson Bay, the town of Churchill in northern Manitoba is unique for its transport infrastructure. With no road access, this community of 870 people hosts the only deep-water port on the Arctic Ocean connected to the North American rail network. Its airport, a legacy of military presence, supports a growing tourism economy. Churchill exists because of these infrastructures—and has changed alongside them. This entanglement becomes especially visible when infrastructure is disrupted. In 2017, flooding destroyed sections of the Hudson Bay Railway, cutting off land access for eighteen months. The disruption triggered shifts in ownership, control, and governance, resulting in one of the few cases worldwide where Indigenous and northern communities collectively own and manage a major Subarctic transport corridor. Ethnographic fieldwork and future scenario workshops reveal how residents of Churchill engage with infrastructure—living with, adapting to, and reimagining it in everyday life. Infrastructure is approached not only as a technical system but as a site of political, affective, and future-oriented engagement. As such, it offers a powerful lens for understanding broader dynamics of change and continuity in (sub)Arctic regions shaped by climate pressures and colonial legacies.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.565
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 studies0.0040.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.049
GPT teacher head0.417
Teacher spread0.368 · 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 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

Citations0
Published2025
Admission routes2
Has abstractyes

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