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Record W3003391565

An Infrastructure Index for Remote Indigenous Communities

2019· article· en· W3003391565 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCSLS Research Reports · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousCensusGeographyMetisIndex (typography)Metropolitan areaSocioeconomicsRemote sensingPopulationMedicineEnvironmental healthEcologySociologyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

This report sheds light on the deficiencies in infrastructure faced by Canada’s remote Indigenous communities by quantifying the level of infrastructure in 236 remote communities in Canada’s North. This quantification is done through a composite index based on 13 infrastructure indicators, including availability of broadband, roads, airports, the electrical grid, health care, education, water, and housing, with values ranging from 0 to 1. This report compares the level of infrastructure found in remote Indigenous communities both with remote nonIndigenous northern communities and southern cities. Indigenous communities are broken down by the three heritage groups: First Nations, Inuit and Métis. While the southern cities identified in the 2016 Census as Census Metropolitan Areas have an average index score of 0.97, remote Indigenous communities saw a score of 0.45 and remote non-Indigenous communities a score of 0.82. Inuit communities face the lowest level of infrastructure (an index score of 0.31), and remote Indigenous communities in Nunavut fared the lowest of the jurisdictions with a score of 0.30.

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.

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)0.004
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 score0.671
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.083
GPT teacher head0.455
Teacher spread0.373 · 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