TAIPEI (TVBS News) — Taiwanese citizens overwhelmingly believe that penalties for fatal child abuse cases are insufficient, according to a survey released Thursday (May 22) by the Action Alliance on Basic Education (國教行動聯盟), a prominent education advocacy group. The poll, conducted over five days from May 17 to 21, gathered 8,724 valid responses with a 48.89% response rate, revealing that more than 90% of respondents consider current punishments too lenient.
The survey reveals a strong public stance on punishment, with an overwhelming 92.1% of participants supporting capital punishment for fatal child abuse cases. Nearly as many respondents — 89.2% — favor life imprisonment without the possibility of parole for those convicted of such crimes. The poll also found significant backing (88.6%) for mandatory psychological treatment programs and comprehensive risk assessments to evaluate the likelihood of repeat offenses among perpetrators.
Li Yu-han (李雨函), who serves as executive director of the alliance's Youth Department, cautioned against purely emotional approaches to criminal sentencing. She emphasized that penalty frameworks must be grounded in evidence, established legal principles, and proportionality standards. Despite this measured stance, Li acknowledged that the overwhelming public support for life imprisonment without parole demonstrates Taiwanese society's clear demand for robust punishment mechanisms in cases involving harm to children.
While acknowledging public sentiment for severe penalties, the alliance emphasized that systematic prevention strategies ultimately deliver greater societal benefits than punishments imposed after abuse occurs. The organization has called on Taiwan's government to implement comprehensive preventative frameworks to protect vulnerable children before harm occurs. This approach aligns with survey respondents' views, as 70.9% expressed support for enhancing child protection systems through mandatory abuse reporting, expanded parental education programs, and stronger community-based prevention networks. ◼
