Project Prairie and Tallgrass Education on the Rice Lake Plains: A Journey from 1870 to Today and Beyond
Bibliographic record
Abstract
Project Prairie began in 2011 as a curriculum-linked integrated environmental studies program to showcase the Rice Lake Plains (RLP), a tallgrass prairie landscape of sandy rolling hills located at the eastern extent of the Oak Ridges Moraine in southern Ontario. Project Prairie provides educators both indoor and outdoor activities that support their curriculum and share the story of the RLP. Project Prairie provides teacher and student resources that focus on the RLP from the mid-nineteenth century to present day. Learning objectives of Project Prairie are developed from the subjects of science, social science, language arts, geography, history, and Aboriginal culture. Additional educational resources that have been produced include a puppet show, maps, an educational booklet with poster, species at risk cards, species at risk booklet, magnets, and a website. The curriculum material can be used on smart boards, thereby giving students the most up-to-date educational experience. Project Prairie grew from successful work completed by Alderville First Nation Black Oak Savanna (ABOS) and other partners in the Rice lake Plains Joint Initiative (RLPJI). The Nature Conservancy of Canada (NCC) forged the multi-partner RLPJI in 2002 to raise awareness and work collaboratively to restore tallgrass prairie and savanna habitats on a landscape scale. To date, the partnership has grown to ten organizations that help deliver Project Prairie to students across the RLP.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".