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Record W7001417238

A Journey Through The Seasons In Anishnaabemowin

2022· other· en· W7001417238 on OpenAlexaboutno aff

Bibliographic record

VenueQSpace (Queen's University Library) · 2022
Typeother
Languageen
FieldComputer Science
TopicData Analysis with R
Canadian institutionsnot available
Fundersnot available
KeywordsPronunciationVowelGlossaryWord (group theory)Word listVowel length
DOInot available

Abstract

fetched live from OpenAlex

This is a four-part mini book series that has been created for level one readers and follows the 
\nfour seasons. The mini-book series will begin with Spring and will progress through the seasons 
\nthat follow. There are 5 pages in each part, included are a title page introducing the season 
\nwith Aanii, and four additional pages with illustrations showing different aspects of what 
\nAnishnaabek does in that season. Each page consists of two or more words, that are not 
\nnecessarily complete sentences so you, the teacher, will have the opportunity to engage the 
\nstudent in creating their own story while learning the Anishinaabe words.
\nThe dialect used is from the Eastern Manitoulin region in Ontario Canada. Each slide comes 
\nwith a teacher prompt. I suggest the teacher say the word in Anishinaabemowin first and students
\nrepeat the word several times. To listen to the voice-over, double-click on the 
\nthumb tack and you will hear how the language is being spoken.
\nThere is also a glossary in the back with translations. Each translated word is broken down into 
\nvowel-constant clusters of syllables that will help with the pronunciation of the Anishnaabe 
\nwords.
\nThe double vowel writing system is used in the text. An explanation of the Double vowel structure 
\nalong with the vowel song is provided so the teacher can practice with the students before going 
\nthrough the reader or for practice at any time. This will help enhance the student’s pronunciation 
\nof each word.

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 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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.197
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0050.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.000

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 head0.009
GPT teacher head0.197
Teacher spread0.188 · 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 teacher head, not a consensus.

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
Published2022
Admission routes1
Has abstractyes

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