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Record W4226056423 · doi:10.32920/19519681.v1

Infrastructure Exposé: Colonialism, Protests, and Logging at Fairy Creek on What is Now Vancouver Island

2022· preprint· en· W4226056423 on OpenAlexaboutno aff
Mei-Ling Patterson

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsColonialismIndigenousCivil disobedienceLoggingState (computer science)EXPOSEPolitical scienceGeographyResource (disambiguation)EthnologyLawHistoryPoliticsEcologyForestry

Abstract

fetched live from OpenAlex

The goal of this assignment was to select a specific infrastructure project in North America and expose its colonial roots. For my assignment, I chose the Fairy Creek Blockade, an ongoing protest being conducted to stop the logging of old-growth forests on Vancouver Island, BC, on the unceded land of the Pacheedaht and Ditidaht First Nations. These protests are now the largest act of civil disobedience in the history of the settler-colonial state of what is currently Canada, and the growth of these protests has been largely due to the influence of social media. Throughout the research I conducted for this assignment, I found that in many ways, it has been the opinions of everyone other than the First Nations whose land this is. These topics have been and continue to be amplified in the media contributing to the ongoing erasure of the Pacheedaht and Ditidaht First Nations communities as well as that of many other Indigenous communities across Turtle Island. There are several colonial roots to this specific infrastructure resource extraction project which I explore throughout my assignment.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.143
Threshold uncertainty score0.289

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0210.004
Scholarly communication0.0060.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.013
GPT teacher head0.294
Teacher spread0.281 · 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
Published2022
Admission routes1
Has abstractyes

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