The global financial crisis and health equity: Early experiences from Canada
Bibliographic record
Abstract
BACKGROUND: It is widely acknowledged that austerity measures in the wake of the global financial crisis are starting to undermine population health results. Yet, few research studies have focused on the ways in which the financial crisis and the ensuing 'Great Recession' have affected health equity, especially through their impact on social determinants of health; neither has much attention been given to the health consequences of the fiscal austerity regime that quickly followed a brief period of counter-cyclical government spending for bank bailouts and economic stimulus. Canada has not remained insulated from these developments, despite its relative success in maneuvering the global financial crisis. METHODS: The study draws on three sources of evidence: A series of semi-structured interviews in Ottawa and Toronto, with key informants selected on the basis of their expertise (n = 12); an analysis of recent (2012) Canadian and Ontario budgetary impacts on social determinants of health; and documentation of trend data on key social health determinants pre- and post the financial crisis. RESULTS: The findings suggest that health equity is primarily impacted through two main pathways related to the global financial crisis: austerity budgets and associated program cutbacks in areas crucial to addressing the inequitable distribution of social determinants of health, including social assistance, housing, and education; and the qualitative transformation of labor markets, with precarious forms of employment expanding rapidly in the aftermath of the global financial crisis. Preliminary evidence suggests that these tendencies will lead to a further deepening of existing health inequities, unless counter-acted through a change in policy direction. CONCLUSIONS: This article documents some of the effects of financial crisis and severe economic decline on health equity in Canada. However, more research is necessary to study policy choices that could mitigate this effect. Since the policy response to a similar set of economic shocks has globally varied and led to differential health and health equity outcomes, comparative studies are now possible to assess the successes and failures of specific policy responses. This raises the question of what types of public policy can mitigate against the negative health equity effects of severe economic recessions.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.043 | 0.011 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".