Exploring Food Insecurity Through Mathematics for Social Justice Lens
Bibliographic record
Abstract
This paper explores the intersection of mathematics education, food insecurity, and social justice, focusing on how mathematics can empower students to critically engage with real-world issues. Grounded in Gutstein’s (2006) “Reading and Writing the World with Mathematics” framework and UNESCO’s Education for Sustainable Development (2020), the study examines how mathematical tasks can foster critical thinking, civic empathy, and social agency. Drawing on data from sources such as the United Nations, the paper highlights the growing global crisis of food insecurity, intensified by conflict, climate change, and inequality. It investigates two central questions: (1) How can mathematical tasks be designed to engage students in analyzing and critiquing food insecurity as a social justice issue? (2) What pedagogical approaches can empower students to use mathematical reasoning to propose solutions to these challenges? The paper presents a structured, phased task that supports both statistical reasoning and critical consciousness, emphasizing localized, and community-based modeling. It concludes by recommending transformative pedagogies that build mathematical competencies and equip learners to act as agents of change in addressing food justice in their communities and beyond.
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How this classification was reachedexpand
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 | 0.001 | 0.016 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".