Bibliographic record
Abstract
In the context of catastrophic climate change, reducing climate implications of food systems is a central challenge. Shifting diets away from meat towards protein-rich pulses reduces climate change-related pressures while offering myriad agronomic benefits. Yet how we produce pulses and not just that we produce pulses matters if those benefits are to be realized. Despite rapid growth, little research on industrial pulse sustainability exists. This research explored connections between world views and food systems in order to assess sustainability claims made by Canada’s industrial pulse sector. First, I distinguished the underlying productivism rooted in mechanistic models and ecologism rooted in holistic models, distinguishing food science from food systems paradigms and how they affect evidence. After contextualizing Canada’s pulse sector, I conducted a discourse analysis revealing shortcomings of conventional narratives on the concepts of choice, efficiency and safety. Next, I analysed eight lock-ins driving Canada’s industrial food system. Finally, I tested two Pulse Canada sustainability claims -- low carbon foot print and soil health—finding these claims ignore the reliance of industrial food systems on 1) petrochemicals and other mined inputs, and 2) excessive fossil energy. Canada’s pulse sector is vulnerable to both ecological shocks associated with industrial production and to social shocks associated with climate unrest and with policy changes that could curtail access to certain pesticides. By forcing pulses to conform to the economics of industrial production, Canada’s farm community bypasses pulses as transition crops toward a truly regenerative agriculture. Given the reality of unavoidable catastrophic climate breakdown, scholars must confront the elephant in the room that is globalized corporate capitalism driving unsustainable approaches to food systems. This paper calls for a radical re-orientation of the economy in the direction of food commons.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.025 | 0.015 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".