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Record W3033116339 · doi:10.1386/btwo_00021_1

Applications and innovations in typeface design for North American Indigenous languages

2020· article· en· W3033116339 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.

Bibliographic record

VenueBook 2 0 · 2020
Typearticle
Languageen
FieldComputer Science
TopicUsability and User Interface Design
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTypefaceIndigenousLinguisticsVisual artsArt

Abstract

fetched live from OpenAlex

In this contribution, we draw attention to prevailing issues that many speakers of Indigenous North American languages face when typing their languages, and identify examples of typefaces that have been developed and harnessed by historically marginalized language communities. We offer an overview of the field of typeface design as it serves endangered and Indigenous languages in North America, and we identify a clear role for typeface designers in creating typefaces tailored to the needs of Indigenous languages and the communities who use them. While cross-platform consistency and reliability are basic requirements that readers and writers of dominant world languages rightly take for granted, they are still only sporadically implemented for Indigenous languages whose speakers and writing systems have been subjected to sustained oppression and marginalization. We see considerable innovation and promise in this field, and are encouraged by collaborations between type designers and members of Indigenous communities. Our goal is to identify enduring challenges and draw attention to positive innovations, applications and grounds for hope in the development of typefaces by and with speakers and writers of Indigenous languages in North America.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.829
Threshold uncertainty score0.215

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.037
GPT teacher head0.280
Teacher spread0.242 · 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