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Record W1547654455 · doi:10.1163/9789004261723

The Green Book of Language Revitalization in Practice

2001· book· en· W1547654455 on OpenAlexaboutno aff
Leanne Hinton, Kenneth Hale

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsLinguisticsSociologyPhilosophy

Abstract

fetched live from OpenAlex

Part I: Introduction L. Hinton, Language Revitalization: An Overview. A. Ash, J. Little Doe Fermino, and K. Hale, Diversity in Local Language Maintenance and Restoration: A Reason For Optimism. Part II: Language Policy L. Hinton, Federal Language Policy and Indigenous Languages in the United States. R.D. Arnold, ...To Help Assure the Survival and Continuing Vitality of Native American Part III: Language Planning L. Hinton, Language Planning. L. Hinton, Introduction to the Pueblo Languages. C.P. Sims, Native Language Planning: A Pilot Process in the Acoma Pueblo Community. R. Pecos and R. Blum-Martinez, The Key to Cultural Survival: Language Planning and Revitalization in the Pueblo de Cochiti. K. Hale, The Navajo Language: I. P.R. Platero, Navajo Head Start Language Study. Part IV: Maintenance And Revitalization of National Indigenous Languages L. Hinton, Introduction to Revitalization Of National Indigenous Languages. L. Hinton, Introduction to the Welsh Language. G. Morgan, Welsh: A European Case of Language Maintenance. K. Hale, Introduction to the Maori Language. J. King, Te Kohanga Reo: Maori Language Revitalization. L. Hinton, Introduction to the Hawaiian Language. S.L. No'eau Warner, The Movement to Revitalize Hawaiian Language and Culture. W.H. Wilson and K. Kamana, Loko Mai O Ka 'I'ini: Proceeding From A Dream - The 'Aha Punana Leo Connection In Hawaiian Language Revitalization. Part V: Immersion L. Hinton, Teaching Methods. L. Hinton, The Karuk Language. T. Supahan and S.E. Supahan, Teaching Well, Learning Quickly: Communication-Based Language Instruction. K. Hale, The Navajo Language: II. M. Arviso and W. Holm, Tsehootsooidi Olta'gi Dine Bizaad Bihoo'aah: A Navajo Immersion Program at Fort Defiance, Arizona. L. Hinton, The Master-Apprentice Language Learning Program. K. Hale, Linguistic Aspects of Language Teaching and Learning in Immersion Contexts. Part VI: Literacy L. Hinton, New Writing Systems. L. Hinton and K. Hale, An Introduction to Paiute. P. Bunte and R. Franklin, Language Revitalization in the San Juan Paiute Community and the Role of a Paiute Constitution. Part VII: Media and Technology L. Hinton, Audio-Video Documentation. K. Hale, Australian Languages. K. Hale, Strict Locality in Local Language Media: An Australian Example. K. Hale, The Arapaho Language. S. Greymorning, Reflections on the Arapaho Language Project, or When Bambi Spoke Arapaho and Other Tales of Arapaho Language Revitalization Efforts. K. Hale, Irish. C. Cotter, Continuity and Vitality: Expanding Domains through Irish-Language Radio. K. Hale, The Mono Language. P.V. Kroskrity and J.F. Reynolds, On Using Multimedia in Language Renewal: Observations from Making the CD-ROM Taitaduhaan. L. Buszard-Welcher, Can the Web Help Save My Language? Part VIII: Training L. Hinton, Training People to Teach Their Language. K. Hale, Inuttut and Innu-aimun. A. Johns and I. Mazurkewich, The Role of the University in the Training of Native Language Teachers: Labrador. L. Hinton, Languages of Arizona, Southern California, and Oklahoma. T.L. McCarty, L.J. Watahomigie, A.Y. Yamamoto, and O. Zepeda, Indigenous Educators as Change Agents: Case Studies of Two Language Institutes. K. Hale, The Navajo Language: III. C. Slate, Promoting Advanced Navajo Language Scholarship. Part IX: Sleeping Languages L. Hinton, Sleeping Languages: Can They Be Awakened? L. Hinton, The Use of Linguistic Archives in Language Revitalization: The Native California Language Restoration Workshop. L. Hinton, The Ohlone Languages. L. Yamane, New Life for a Lost Language. About the Editors. About the Authors. Index.

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)0.003
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.027
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.004
Science and technology studies0.0030.009
Scholarly communication0.0100.010
Open science0.0020.005
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0270.010

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 head0.043
GPT teacher head0.476
Teacher spread0.433 · 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

Citations825
Published2001
Admission routes1
Has abstractyes

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