A Community Compost Exchange Manual: reconnecting municipal organic waste and soil management
Bibliographic record
Abstract
Ontario’s Provincial waste strategy and Toronto’s long term-waste management plan both clearly recognize that the multi-residential sector holds the greatest opportunity for increased participation and decreased contamination in waste collection. With this in mind, A Community Compost Exchange Manual: reconnecting municipal organic waste and soil management was made to highlight the impacts and connections a community-based waste management (CBWM) project has to the multi-faceted issues facing multi-residential waste diversion. This manual uses a collection of essays as a framework to connect different elements of (CBWM) to greater schematic themes impacting organics recycling in Ontario and Toronto. The work can be read sequentially, or each section can be read as a stand-alone piece that dives into the academic and experienced-based aspects of the Community Compost Exchange (CCE) an organics recycling program in Toronto. A methodology comprising of literature reviews, analyses from participant surveys, qualitative data through interviews and personal communications with current Toronto composters, and personal experiences of managing and scaling up the CCE are used to inform this work. The manual starts with a soil acknowledgment that centers Indigenous knowledge and its contributions to composting and soil management. Then the programs goals and intentions are addressed in its mission statement along with the collected statistics beginning in 2015. \nFollowing that, an essay on current food waste diversion programs and techniques being utilized by Solid Waste Management Services of Toronto and local community groups is organized within a food waste hierarchy structure. This analysis shows that community initiatives do most of the work for preferred diversion methods but proportionally, are very under-supported by current municipal budgets. Then, the major components of the CCE are described in detail through three essays: 1. knowledge sharing and food justice at urban farm markets; 2. Incentivization of organics participation; and 3. best practices for processing municipal waste into nutrient dense compost for use in agricultural soils. Finally, an in-depth look at the policies impacting community composting, from the federal to municipal levels, identifies solutions and produces policy recommendations to grow decentralized composting across Ontario. Waste touches deeply on both social, political, economic, ecological and justice-based issues, which is why this manual works to thoroughly place the Community Compost Exchange into a diverse dialogue with these issues.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.040 | 0.010 |
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".