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Record W6912035994 · doi:10.5281/zenodo.14267791

Projected speaker numbers and dormancy risks of Canada's Indigenous languages

2024· dataset· en· W6912035994 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousTable (database)PopulationCode (set theory)Range (aeronautics)

Abstract

fetched live from OpenAlex

Data and code for the paper "Projected speaker numbers and dormancy risks of Canada’s Indigenous languages". Contain speaker numbers by age and language (Indigenous mother tongue, unique responses). There is one file per year (2001, 2006, 2011, 2016, 2021). Data were provided by Statistics Canada. These include: - indigenousmothertongue2001.csv- indigenousmothertongue2006.csv- indigenousmothertongue2011.csv- indigenousmothertongue2016.csv- indigenousmothertongue2021.csv Additionally, the file 'coordinates.xlsx' contains the geographic coordinates necessary for Fig. 1. Information comes from Ethnologue with modifications. Also included is the life table information produced by World Population Prospects 2024 (wpp 2024 files) available at https://population.un.org/wpp/Download/Standard/Mortality/. These are provided here for convenience as well as to prevent updates by the WPP. Also contains the whole R code to produce the results described in the paper (RevisedScript_ProjectCanIndigLangs_Final.R).

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.062
Threshold uncertainty score0.206

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.013
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0620.023

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 head0.034
GPT teacher head0.286
Teacher spread0.251 · 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 designObservational
Domainnot available
GenreDataset

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

Citations1
Published2024
Admission routes1
Has abstractyes

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