Children’s attitudes towards animal cruelty: Exploration of predictors and socio-demographic variations

ABSTRACT

Assessing the risk for animal cruelty is imperative, yet understudied and problematic due to the sensitivity of the topic. Early prevention is critical, yet very little research examines cruelty when it first appears in childhood. The aim of this study was to explore children’s attitudes towards types of animal cruelty, to investigate potential demographic differences, and to examine potential associations between acceptance of cruelty and cognitive and affective factors that place children ‘at-risk’ for cruelty perpetration. Questionnaire data was collected from 1127 children in schools. The results indicate that cruelty attitudes are predicted by some demographic variables such as urban living, being male, younger age and not having pets, but depend on the type of animal cruelty. Acceptance of cruelty predicted low compassion and low reported humane behaviour towards animals. Acceptance of cruelty was predicted by negative attitudes towards animals, lower beliefs in animal minds and low attachment to pets, signifying the importance of targeting such variables in future prevention programmes. This study is an original contribution to research into childhood animal cruelty in the general population, with implications for designing and implementing early prevention programmes that tackle problematic attitudes to cruelty.     

Learning from each other: causal inference and American political development

Public Choice - Within political science, a movement focused on increasing the credibility of causal inferences (CIs) has gained considerable traction in recent years. While CI has been...     

Inclusivity in Online Platforms: Recruitment Strategies for Improving Participation of Diverse Sociodemographic Groups

Governments are increasingly implementing smart and digital approaches to promoting citizen participation. However, whether online participation platforms are tools that improve inclusivity in citizen participation remains underexplored. To address this gap, this article focuses on the role of recruitment messages and their effect on participation in an online participation platform by gender and age. A field experiment with a neighborhood census sample (N = 6,066) shows that online participation dips for younger and older citizens and is equal among women and men. For the age groups between 60 and 75, differences in the control and intervention recruitment messages significantly impacted participation. These findings can help public managers tailor recruitment strategies to facilitate inclusive participation and represent a first step toward learning what types of messages are effective for whom.     

The future of crime data

Criminology lacks sufficient data for many types of crime that are of great concern to society. This lack of data poses significant problems for determining whether resources are adequate for responding to these crimes or whether programmatic, legislative, or target-hardening efforts to prevent or reduce their occurrence are effective. Inadequate data about crime also produces a selective and incomplete narrative about crime that makes it easier for political and vested interests to exploit public concerns about crime for their own ends. In this address, I discuss what is needed to resolve these gaps and the ways in which criminologists can support a significant expansion of the crime data infrastructure. Such work is necessary to help ensure the future relevance of criminological research.     

Metric forensic anthropology decisions: Reliability and biasability of sectioning-point-based sex estimates

Subjective decisions make human cognitive processes more susceptible to bias and error. Specifically, research indicates that additional context biases forensic anthropologists’ morphological analyses. To address whether metric analyses are also subject to bias, we conducted a pilot study in which 52 experienced osteologists measured a difficult-to-classify human femur, with or without additional contextual information. Using a metric sectioning-point sex-estimation method, participants provided a sex estimate for individual skeletal element(s) and, when given multiple elements, the combined skeletal assemblage. Control group participants (n = 24) measured only the femur. In addition to the femur, bias group participants (n = 28) either measured a female humerus and viewed a female-biasing photograph (n = 14) or measured a male humerus and viewed a male-biasing photograph (n = 14). We explored whether the experts in the different groups would differ in: (1) femoral measurements; (2) femoral sex-estimation conclusions; and (3) final sex-estimation conclusions for the skeletal assemblage. Although the femoral measurements and femoral sex estimates were comparable across groups, the overall sex estimates in the female-biased group were impacted by contextual information—differing from both the control and male-biased groups (p < 0.001). Our results demonstrate that cognitive bias can occur even in metric sex-estimation conclusions. Specifically, this occurred when the metric data and single-element sex estimates were synthesized into an overall estimate. Thus, our results suggest that metric methods are most vulnerable to bias when data are synthesized into an overall conclusion, highlighting the need for bias countermeasures and comprehensive statistical frameworks for synthesizing metric data to mitigate the effects of cognitive bias.     

The erosion of the administrative state under President Trump: Citizens' pushback against individual and institutional racism

President Trump encouraged bad state actors within the administrative state to contribute to inequities for civilians. We highlight how Trump's actions and rhetoric led to increased individual, institutional, and systemic racism and violence. As a response to this increased violence and rhetoric, we discuss the role civilians (including professional athletes) played in engaging in protests and the 2020 election. Given that more individuals voted in that election cycle, we emphasize the importance for public administration to adapt, evolve, and engage with new actors concerned with administrative action or inaction.     

Managing policy‐making in the local climate governance landscape: The role of network administrative organizations and member cities

Trans‐municipal networks (TMNs) have reshaped the landscape around local government action on global climate policy. Past research has focused on why cities join TMNs and the impact that membership has on local action. This study considers a potential reverse effect: namely, that cities' membership choices position them to influence TMNs' overall priorities. In considering this, we emphasize the role of network administrative organizations (NAOs) and posit that the multiple climate‐related networks, which share members and operate in overlapping geographic and issue spaces, are bound together as part of a meta‐network. We utilize social network analysis and data on membership in four climate‐related TMNs to examine the factors that shape how cities can influence meta‐network priorities. We find that cities with local vulnerabilities tend to be located in network positions that enable them to influence the meta‐network's overall priorities.