Diet for a Better World: Exploring the Intersectional Impact of Meat-based vs Plant-Based Diets and First Steps for Change
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Humanity is faced with numerous pressing issues from the health crisis and human rights violations to climate change and animal cruelty. Although various methods are being employed to solve these issues, dietary changes are often overlooked. Unbeknownst to many people, the meat, dairy and fish industries continue to play a substantial role in perpetuating environmental degradation, animal cruelty, and human rights issues. However, the adoption of a 'plant-based' or 'vegan' diet emerges as a powerful catalyst for yielding widespread change in these issues. This research paper aims to explore the importance of transitioning society away from animal-based diets and towards plant based meals. Addressing a spectrum of urgent issues, this paper underscores the often underestimated potential of transitioning to plant-based diets as a potential solution to human, animal and environmental issues. The paper commences with a meta-analysis, employing an intersectional lens of human ethics, animal ethics, environmental concerns, and health perspectives, to evaluate the negative repercussions of animal agriculture industries. Perceived negatives of plant-based diets will then be explored to holistically conceptualize whether veganism is a valid and feasible option for individual and societal change. Lastly, drawing from prior studies and acknowledging the barriers of transitioning to a plant-based lifestyle, the paper culminates in proposing first steps for creating a successful plant-based transition: the implementation of plant-based meals and education in schools.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it