San Diego Doctor Who Doled Out 1,000 Vaccine Exemptions Faces Medical Board Charges

A San Diego doctor who has written an estimated 1,000 vaccine exemptions since 2015 is facing charges of repeated negligence from the Medical Board of California. Dr. Tara Zandvliet is San Diegos biggest doctor for the anti-vaxxer movement, especially in the citys schools, where shes written the Voice of San Diego, accusing her of gross and repeated negligence, failure to maintain records, and unprofessional conduct. In 2016, the father of a four-year-old girl sought Zandvliets help exempting his daughter from vaccines, according to the state complaint filed this month. The girl, referred to as Patient A, had already received some vaccinations, with none of the adverse effects that the anti-vaccination movement claims can come with immunization. Nevertheless, Patient As father …

How Sex-Trafficking Survivors Are Locked Out of Victim Funds

Deborah Pembrook doesnt remember exactly when she was first sex-trafficked, but she knows it was earlythe images of abuse collide in her brain with images of childhood crayons and stuffed animals. When she finally escaped, she was 17 years old and all alone. Her earnings had gone to her trafficker, so she had no savings, and she was forced to move to another state, so she had no family or safety net. And because of the laws in Californiathe state where she eventually settled, to disappear among tourists on the crowded beaches of Santa Cruzshe had no way of getting what she really needed: cash. Throughout the United States, thousands of human-trafficking survivors are struggling to make up for the …

Researchers spotlight the lie of anonymous data

Researchers from two universities in Europe have published a method they say is able to correctly re-identify 99.98% of individuals in anonymized data sets with just 15 demographic attributes. Their model suggests complex data sets of personal information cannot be protected against re-identification by current methods of “anonymizing” data — such as releasing samples (subsets) of the information. Indeed, the suggestion is that no “anonymized” and released big data set can be considered safe from re-identification — not without strict access controls. “Our results suggest that even heavily sampled anonymized datasets are unlikely to satisfy the modern standards for anonymization set forth by GDPR [Europe’s General Data Protection Regulation] and seriously challenge the technical and legal adequacy of the de-identification …