Bibliographic record
Abstract
I grew up running around the gardens in Old Perlican.Dodging the hens and roosters, watching the fishermen trench the rows and toss in capelin and cod guts for fertilizer.Playing hide-and-seek in root cellars, amongst the pickles, preserves, and corned fish.It was a way of life.If you wanted to eat in Newfoundland, you had to grow and gather your food.We have survived for generations this way.Everything was organic before it became the loose term used to describe almost anything nowadays.Then came the modern supermarkets and the big-box stores.We lost our way for a bit, at least my generation had.Everything was more convenient, accessible, and "fresh."After living with food that comes from all corners of the globe, food that is modified, treated, and altered, we now find ourselves going back to our roots, to our gardens.Over the last few years Newfoundland has seen its agricultural heritage start to re-emerge.I get great pleasure in opening my kitchen door at Raymonds and greeting one of the many purveyors.It could be beautiful lamb from the southern shore, raised by the Morrys or the Mooneys.Vegetables from Mike Rabinovitz or Mary Lester, here on the Avalon, or maybe fresh seafood from Gerry Hussey in Bonavista.Every day it seems someone else has started a new venture in agriculture, inspired by previous generations, or maybe they just took a walk through the Pattersons' garden in Upper Amherst Cove and fell in love like I do every time I visit.This book shows us how great and unique our history of agriculture is in Newfoundland.It's inspiring our cooks, our farmers, and the next generation.Sustainable eating and living is possible in this province, and we have the history to prove it.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.749 | 0.744 |
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".