“We like to be in the tent”: How charitable organizations navigate political advocacy for health equity
Bibliographic record
Abstract
Globally, charitable organizations vitally advocate for health equity by addressing social-structural determinants like income inequality, housing insecurity, and systemic discrimination through political activities, coalition building, and direct interventions. This article examines the discursive, legislative/political, and organizational elements shaping the political activities of charities working to transform the social-structural determinants of health and health inequity in Ontario, Canada. We conducted 28 in-depth interviews with staff from 24 charities addressing social-structural issues, including harm reduction, mental health, disability rights, migrant justice, housing access, and integrated social services. Drawing on Situational Analysis, our findings reveal that some charities' pursuit of political advocacy and activism against root causes of health inequities aligns with their discursive framing as agents of democratization, while the reluctance and self-imposed restrictions of other charities reflects the framing of charities as (non)compliant and (in)competent. Federal regulations and provincial political regimes continue to influence the ability of charities to challenge structural barriers, often through funding dynamics. Organizational elements including size, scope, leadership, capacity, and budgeting further shape political engagement around social-structural change. We argue these elements are undergirded by neoliberal governance, leading some charities to prioritize efficiency and accountability to funders over systemic equity and social justice, and reflect broader trends in governance that constrain civil society's capacity to address health inequities Despite these factors, many charities balance organizational responsibilities with transformative aims. Supporting the democratic role of charities thus requires adequate funding, resources, and capacity building to enable them to tackle entrenched structures of health inequity while maintaining essential services.
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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 | 0.048 | 0.101 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.063 | 0.053 |
| Scholarly communication | 0.037 | 0.029 |
| Open science | 0.004 | 0.028 |
| Research integrity | 0.030 | 0.036 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".