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Record W1542323009 · doi:10.15353/joci.v10i2.2725

From the First Mile to Outer Space: Tamaani Satellite Internet in Northern Quebec

2013· article· en· W1542323009 on OpenAlexaffvenueabout
Rob McMahon, Thomassie Mangiok

Bibliographic record

VenueThe Journal of Community Informatics · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovative Approaches in Technology and Social Development
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsGovernment (linguistics)Last mile (transportation)MileGeographyPoliticsBroadbandThe InternetBusinessInternet accessEconomic growthPolitical scienceTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

Across Canada, discrepancies of access to broadband exist between urban centres and rural and remote Aboriginal communities. Government, public and private sector organizations are partnering to address these digital divides. Some employ a ‘First Mile’ approach that foregrounds how community-based institutions are driving development. This article provides a First Mile case study from the Inuit territory of Nunavik. We describe the cultural, social and political contexts the people of Nunavik and their government navigated to establish broadband in the region’s 14 northern villages. The Kativik Regional Government is building and administering infrastructure that delivers public services and encourages economic development, balancing centralized efficiencies with the needs of residents in villages like Ivujivik.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.054
Threshold uncertainty score0.395

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0140.002
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.023
GPT teacher head0.226
Teacher spread0.203 · 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

Citations4
Published2013
Admission routes3
Has abstractyes

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