Bibliographic record
Abstract
There are so many stories out there of how people come to farming - whether it's first generation, or intergenerational. The fascinating yet frustrating thing is these stories are almost all different. There doesn't seem to be a simple, tried and true path to farming. Frustrating too, because the tips and strategies of the 'how' are hard to hear and tease out. The crew tries to do just that, focusing on finding the high-level nuances of those strategies, while attempting to build a list of tips for those stuck in the complexity of doing something that feels hard on a good day. A special thank you to the many, many farmers and farm workers who sat down to share their stories with us. One of the hardest choices of the season was choosing which made it into the show. Thank you again, and to those reading, listen to your farmers - their stories are ones of perseverance, strength and resilience, and certainly sources of great hope. LINKS Tackling Transitions: Informing a New Food Systems Planning Strategy for Ontario / IG @farmerclairesfoodfun Crocus Hill Garden / IG: @crucushillgarden Wildwood Farm IG: @chigarden2015 / FB: Chi Garden
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.006 |
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; both teacher heads agree on what is shown here.
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".