Social Sustainability Assessment of Canadian Egg Production Facilities: Methods, Analysis, and Recommendations
Bibliographic record
Abstract
A detailed assessment of the “gate-to-gate” social risks and benefits of Canadian egg production facilities was undertaken based on the United Nations Environment Programme/Society of Environmental Toxicology and Chemistry (UNEP/SETAC) Guidelines for Social Life Cycle Assessment. Data were collected via survey from a representative subset of Canadian egg farms, and evaluated against a novel suite of indicators and performance reference points developed for relevance in the Canadian context. The evaluation focused on interactions with four stakeholder groups (Workers; Local Communities; Value Chain Partners; and Society) in eighteen thematic areas. This assessment resulted in a rich and highly nuanced characterization of the potential social risks and benefits attributable to contemporary egg production facilities in Canada. Overall, risks were low and benefits were identified for Local Communities, Value Chain Partners, and Society stakeholder groups, but mixed for the Workers stakeholder group. With respect to the latter, identified areas of higher risk are related, in particular, to a subset of indicators for Working Hours, Equal Opportunities and Fair Salary. As such, the results suggest opportunities and strategies for the Canadian egg industry both to capitalize on its current successes as well as to proactively engage in improving its social sustainability profile. The study also contributes a novel set of social sustainability metrics for use and continued development in the Canadian egg sector as well as other agri-food sectors in Canada and beyond. The inevitable challenge in social life cycle assessment (LCA) of developing non-arbitrary performance reference points for social indicators for which clear norms do not exist, and similarly for establishing non-arbitrary scales and thresholds for differentiating between performance levels, is underscored. A necessary next step with respect to the methods presented herein is for stakeholder groups to carefully consider and refine the performance reference points and characterization thresholds that have been developed, in order to assess their alignment with context-specific social sustainability priorities for this industry, and also to extend the analysis to encompass other value chain stages to enable a full social life cycle assessment.
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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 | 0.028 | 0.041 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".