The price of development: The importance of preserving local agricultural lands
Bibliographic record
Abstract
Regardless of the fact that we have long been warned of the negative impact of industrial farming, rural communities are being wiped out as local producers, like Riverbend Gardens, are put at risk in favour of urban expansion. The industrial food production industry is unsustainable, leading to increased energy consumption and food costs because of the gross use of energy to transport food hundreds kilometres from where it is produced. Toxic chemicals used to combat swarms of pests that are nurtured by acres of single crop farming have lead to the increase of these substances in our environment. The growing disconnection between ourselves and how our food is produced, fostered by diminishing farm communities, allows us to continue as we always have, until our current system collapses. This will have a deleterious effect on our health and our environment. Many of the answers to the problems we face in our food production industry lies in support for our small, local food producers. Located within Edmonton city limits, sustainable, family run, Riverbend Gardens, is at risk of being wiped out if government and consumers do not recognize the importance of small producers and their part in solving the food industry’s failures.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 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".