A Journey Through The Seasons In Anishnaabemowin
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.053 | 0.014 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".