“Lucy says today she is a Labordoodle”: how the dogs-of-Instagram reveal voter preferences

Instagram is an image-centric social media application, launched in October 2010 with the explicit aim of allowing members to share their smart phone photos with the world. Posts typically combine photographs with a short verbal text, and as such provide fertile ground for multisemiotic analysis. Further, at times of political significance or upheaval, Instagram, like other social media platforms, provides a space for the public to express opinions or emotions. The fact that citizens do this through a combination of words and images on Instagram is the subject of analysis in this article. Using a dataset of 92 Instagram posts that made use of the discourse tagging hashtag #dogsatpollingstations at the time of the 2016 Australian federal election, this study demonstrates the multisemiotic strategies used by members of the public to show their dissatisfaction with the incumbent government, and their endorsement of other political parties. The study also demonstrates the triangulation of multiple methods, and as such is an example of corpus-assisted multimodal discourse analysis.     

Homeland and its use of bipolar disorder for sensationalist and dramatic effect

When a lead character in a critically acclaimed and award-winning television programme is depicted as a proficient and meticulous heroine with a mental disorder, it is crucial to examine if this reflects a change in the media depiction of people with mental illness. This article employs framing analysis to examine the portrayal of lead CIA agent with bipolar disorder, Carrie Mathison, in Homeland. Although the show did initially associate competence, intellect and astuteness to this character, as it progressed, the framing decisions used for dramatic and sensational purposes ultimately presented Mathison within the usual stereotypical depictions: as impulsive, irrational, unpredictable, unstable, dangerous and disordered. Given the popularity of the show, responsible depictions should take priority over dramatic effect at the expense of a character with mental illness because sufferers may be deterred in speaking about their illness and seeking appropriate treatment if such negative themes persist.     

Regulating Autonomy: An Assessment of Policy Language for Highly Automated Vehicles

Self‐driving cars (also known as driverless cars, autonomous vehicles, and highly automated vehicles [HAVs]) will change the regulatory, political, and ethical frameworks surrounding motor vehicles. At the highest levels of automation, HAVs are operated by independent machine agents, making decisions without the direct intervention of humans. The current transportation system assumes human intervention though, including legal and moral responsibilities of human operators. Has the development of these artificial intelligence (AI) and autonomous system (AS) technologies outpaced the ethical and political conversations? This paper examines discussions of HAVs, driver responsibility, and technology failure to highlight the differences between how the policy‐making institutions in the United States (Congress and the Public Administration) and technology and transportation experts are or are not speaking about responsibility in the context of autonomous systems technologies. We report findings from a big data analysis of corpus‐level documents to find that enthusiasm for HAVs has outpaced other discussions of the technology.     

Political Brand Communities as Social Network Clusters: Winning and Trailing Candidates in the GOP 2016 Primary Elections

This study integrates a brand community theoretical framework and a social networks approach to the study of political marketing on social media. It analyzes Twitter activity by and about all Republican candidates during the month of January 2016 prior to the Iowa primary caucus. Specifically, it identifies key patterns of information flow and political brand community emergence surrounding each candidate as well as brand social mediators who play influential roles in content flow. Findings detect network clusters - subgroups of siloed users - who converse to exchange information with one another rather than with disconnected others in any given political brand community. We classify these clusters in two groups: direct communities that surround a brand – here, a candidate – and indirect communities that consist of users who talk about the political brands but are not directly connected to the brand. Within this fragmented community structure, brand social mediators have the power to bridge direct and indirect brand communities across the network. Among the winning and trailing brand communities, different sets of brand social mediators, patterns of information flow, and network structures emerge. The findings suggest that the more successful a political brand is in voter polls, the weaker the social ties and relationships are within the brand communities. The interactions between political brands and their direct vs. indirect communities also exhibit different patterns of information flow. While direct brand communities demonstrate a higher level of reciprocity, indirect brand communities show a higher level of density. Implications and directions for future research are discussed.     

Designing for equitable civic engagement: Participatory design and discourse in contested spaces

A common theme of research on participatory democracy and citizen engagement centres on the need for empirical studies that conduct a deep exploration of the nuances and complexities of these processes. This article offers a distinct response to this need through an examination of two ethnographic case studies of a participatory budgeting process in a multilingual, highly diverse community in which Spanish-speaking Latino immigrants were involved. By analyzing participants discourse from the case studies, the findings highlight the risks and rewards of reframing participatory processes as design decisions rather than static procedures.     

域外毒品鉴定错案成因分析与防范借鉴

近年来,域外毒品鉴定错案高发,深刻暴露出毒品鉴定管理的内源性问题,值得我国相关领域工作人员借鉴。本文首先概述了毒品鉴定的特点;其次,根据近年来美国、加拿大、英国等地出现的典型毒品鉴定错案,对相关成因做系统梳理,为提升毒品鉴定管理质量、降低毒品鉴定错案的负面影响提供参考依据。本文将鉴定错案分为"错误"和"失误"两大类,并提出了通过提升实验室内部管理、加强实验室外部监督以及落实鉴定意见的质证认证等环节,预防毒品鉴定错案的系统方法。对于防范毒物毒品错案的发生具有重要的参照意义。     

Simulation-based reconstruction of traffic incidents from moving vehicle mono-camera

Video recordings from digital cameras implemented in road vehicles present a valuable source of data concerning various dangerous traffic situations, i.e., road accidents or near-miss incidents. This data is readily available and numerous methods for forensic reconstruction of traffic situations from vehicle video were presented in the past. New alternative method for reconstruction of traffic situations from vehicle video is presented in this article. The method is based on the fusion of kinetic vehicle trajectory simulation within 3D laser scanner point cloud, projective geometry, and processing of video footage from moving vehicle camera. The method offers accurate reconstruction of general vehicle motion within relevant time domain whereby in-depth technical information about traffic incident can be quantitatively extracted from video footage. The result is physics-based 3D projection of simulated vehicle motion on the motion of real vehicle recorded by moving monocular camera. The method was validated within performed experimental test runs with respect to vehicle speed, distance travelled, acceleration/deceleration and directional quantities (yaw rate, yaw angle). The method was further applied in the reconstruction of real-world traffic events.     

刍议法律的经济分析理论结构

法律的经济分析理论自产生发展至今,已成为法学理论的一个重要分支,要想正确认识和运用这一理论,必须对其理论结构进行详细的研究。法律的经济分析理论结构包括四个方面,即法律的经济分析理论的内涵、法律的经济分析理论的哲学基础、法律的经济分析遵循的原则、法律的经济分析的方法和基本定理。     

论民警培训需求分析的运行机制建设

民警培训需求分析是生成民警培训计划的前提和基础,它对实现培训价值和教育训练民主,提高民警培训质量具有重要意义。民警培训包括干部培训和警察职业教育活动,开展培训需求分析应兼顾公安队伍建设、公安机关履职能力提升和民警个人职业发展的需要,从需求分析目标、组织机构、分析方法、反馈机制等方面探索需求分析的运行机制,实现需求分析的常态化、规范化。     

专利药品价格影响要素的实证分析——基于美国1999年至2010年的数据分析

随着医疗改革的不断深入，专利药品价格已成为国内外学界和产业界关注的焦点。本文利用1999年至2010年美国面板数据对专利药品价格影响要素进行了实证分析，结果显示，专利保护期限、仿制药价格、人均国内生产总值对专利药品价格变动具有显著影响。在此基础之上提出相关的政策建议。