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Record W7098569785

Must There Be Two Solitudes? Language Activists and Linguists Working Together

2013· article· en· W7098569785 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell Image Analysis Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousDramaReciprocity (cultural anthropology)PhraseNationalismIndigenous languageOrder (exchange)
DOInot available

Abstract

fetched live from OpenAlex

This paper suggests that there can be two solitudes that divide linguists and language activists and argues that there needs to be a mutual recognition that linguists and Indigenous communities need to work together to help revitalize Indigenous languages. It takes a community of people to revitalize an Indigenous language, and in order for linguists and language activists to truly work together, general principles such as relationships, respect, reciprocity and recognition are critical. In Canada, there is a phrase that is sometimes used to signify the relationship between English-speaking Canada and French-speaking Canada, two solitudes. This term was popularized by Hugh MacLennan in the title of his 1945 novel, Two Solitudes. The publisher’s blurb for this book says the following: A landmark of nationalist fiction, Hugh MacLennan’s Two Solitudes is the story of two races within one nation, each with its own legend and ideas of what a nation should be. In his vivid portrayals of human drama in prewar Quebec, MacLennan focuses on two individuals whose

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)0.023
metaresearch head score (Gemma)0.027
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: none
Teacher disagreement score0.035
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0350.061
Scholarly communication0.0250.029
Open science0.0020.022
Research integrity0.0120.021
Insufficient payload (model declined to judge)0.0110.002

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 head0.009
GPT teacher head0.281
Teacher spread0.273 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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