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Record W4244617787 · doi:10.5325/jinfopoli.7.1.0423

Reclaiming Geospatial Data and GIS Design for Indigenous-led Telecommunications Policy Advocacy: A Process Discussion of Mapping Broadband Availability in Remote and Northern Regions of Canada

2017· article· en· W4244617787 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Information Policy · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicGeographic Information Systems Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGeospatial analysisWorkflowBroadbandComputer scienceGeographic information systemProcess (computing)Geospatial PDFGIS applicationsTelecommunicationsRemote sensingGeographyDatabase

Abstract

fetched live from OpenAlex

Abstract Geographic Information Systems (GIS) and geospatial data are important advocacy tools adopted by a range of users, including telecommunications policy advocates. However, without the means to actively deconstruct and reshape such platforms, reclaim the geospatial data they utilize, and generate the visualizations they produce, the increasing adoption of these resources threatens to disempower some community-based user groups. In this article, we argue that the processes used to design such tools for policy advocacy must transparently reflect the socially constructed nature of the GIS systems and the geospatial data visualizations they generate, as well as the values and goals of the specific user groups they are designed to support. We ground this argument in a case study of a regulatory hearing on telecommunications infrastructure and services in Canada, and introduce a freely available online resource that documents our GIS design workflow in more detail.

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)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.550
Threshold uncertainty score0.881

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0010.000
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 head0.042
GPT teacher head0.336
Teacher spread0.294 · 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