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Record W7010840242

Language Funding Inequity Irks Inuit Google Maps Adds Indigenous Communities

2017· other· en· W7010840242 on OpenAlexaboutno aff

Bibliographic record

VenueBulletin of Miscellaneous Information (Royal Gardens Kew) · 2017
Typeother
Languageen
FieldMathematics
TopicProbability and Statistical Research
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousEquity (law)Indigenous languageGovernment (linguistics)The Internet
DOInot available

Abstract

fetched live from OpenAlex

This week... When words fail: Especially when one hears about the enormous equity gap in federal funding between French and Inuit languages in Nunavut. Plus... Putting us on the mapliterally. Google announces that users of its Maps app will now get to see thousands more Indigenous communities. But will that hide as much as it reveals? Back again at the roundtable are Karyn Pugliese, APTN's Executive Director of News and Current Affairs, plus Lisa Girbav, a radio broadcaster and student from the Tsimshian territory.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.869
Threshold uncertainty score0.994

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.001
Scholarly communication0.0070.005
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.2970.041

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 head0.036
GPT teacher head0.287
Teacher spread0.250 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2017
Admission routes1
Has abstractyes

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