‘It’s Been a Huge Stress’: An In-Depth, Exploratory Study of Vaccine Hesitant Parents in Southern California
Bibliographic record
Abstract
In 2015, the US experienced a widespread measles outbreak that originated at Disneyland, California and spread to six other states, Mexico, and Canada. That year, California passed Senate Bill 277 (SB 277), which eliminated the personal belief exemption for vaccinations required for school entry; California became the third state in the country to eliminate nonmedical exemptions. In 2019, Washington, Maine, and New York followed suit eliminating all nonmedical exemptions amid the largest measles outbreak in the US in 25 years. Many countries, including the US, are experiencing a rise in vaccine preventable diseases due, in part, to increasing vaccine hesitancy, a fluid and context- and vaccine-specific phenomenon broadly defined as the delay or refusal of vaccine services despite availability. Through in-depth interviews with vaccine hesitant parents in Southern California, this dissertation explores the underlying factors that shape vaccine hesitancy and examines how the passage of SB 277 impacted vaccine-related strategies, decisions, and behaviors. Applying a political economic framework through a feminist lens, three major themes are presented, 1) highly individualized processes of risk assessment and management around vaccines, informed by neoliberal ideologies, 2) institutional distrust that drives parents to challenge biomedical authority and demedicalize their approaches to health, and 3) the gendered processes of vaccine hesitancy that disproportionately burden women and mothers. Findings suggest that efforts aimed at addressing falling vaccination rates and subsequent vaccine-preventable disease outbreaks would benefit from in-depth, qualitative research that considers multiple socio-ecological levels of influence, including interpersonal, socio-cultural, and political economic.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".