食品安全报道的传媒责任——“老酸奶”事件中的媒体呈现及其反思

由名人微博爆料引发的“老酸奶”事件,由于涉及整个社会极为关注的食品安全话题,经过作为新媒体典型代表的微博的广泛传播和传统媒体的推波助澜,一时间引发公众广泛议论,几近酿成公共危机事件.然而,由于始终未得到证实或证伪,成为一起少见的有始无终的传播事件.媒体应该反思在这起事件中的呈现,提升食品安全报道的“净化力”,强化食品安全报道能力,实现食品安全报道的日常化,以提升公众对于突发食品安全事件的风险感知与辨别能力.     

Classification Algorithm for Skin Color (CASCo): A new tool to measure skin color in social science research

Objective

A growing body of literature reveals that skin color has significant effects on people's income, health, education, and employment. However, the ways in which skin color has been measured in empirical research have been criticized for being inaccurate, if not subjective and biased.

Objective

Introduce an objective, automatic, accessible and customizable Classification Algorithm for Skin Color (CASCo).

Methods

We review the methods traditionally used to measure skin color (verbal scales, visual aids or color palettes, photo elicitation, spectrometers and image-based algorithms), noting their shortcomings. We highlight the need for a different tool to measure skin color

Results

We present CASCo, a (social researcher-friendly) Python library that uses face detection, skin segmentation and k-means clustering algorithms to determine the skin tone category of portraits.

Conclusion

After assessing the merits and shortcomings of all the methods available, we argue CASCo is well equipped to overcome most challenges and objections posed against its alternatives. While acknowledging its limitations, we contend that CASCo should complement researchers. toolkit in this area.