轻微犯罪刑事政策的具体运用

应对轻微犯罪与重刑犯罪分别适用不同的刑事政策,以暂缓起诉等人文关怀方式挽救和感化轻微犯罪人,促使其尽快复归社会,实现社会治安的良性循环.立足于非犯罪化和非刑罚化的实现途径,一要实现轻微犯罪的非刑罚化和刑罚个别化;二要强化犯罪嫌疑人的权利保障意识,改变以逮捕为主导的候审羁押制度.     

打破政策“黑箱”的制度设计——基于广州政策兑现实践的研究

如何打破政策“黑箱”是学界和社会关注的重要议题。以广州市政策兑现改革实践为例,探讨如何从制度设计层面来打开公共政策过程中的政策“黑箱”。研究发现,虽然公共政策过程是一个动态且复杂的过程,但是通过统筹政策制定和政策落地两端、主观要素客观化、模糊标准明确化、重塑政府流程等,能够形成确定的决策环境,控制非理性因素,约束自由裁量权,并压缩权力寻租空间,从而可以从源头消除政策“黑箱”的形成土壤。广州市政府政策兑现改革过程中,通过“输入—转化—输出”的制度框架设计,形成了从政策制定到政策执行再到政策结果与评估的政策闭环,并对政策兑现的相关责任单位、流程和时限都进行了严格把控,进而实现对政策“黑箱”内部决策要素的控制。从政策“黑箱”本身入手,破解政策“黑箱”难题,实现政策的阳光承诺和给付,最终形成极具特色和借鉴意义的广州模式。     

Policy Adoption and Policy Intensity: Emergence of Climate Adaptation Planning in U.S. States

The United States is experiencing growing impacts of climate change but currently receives a limited policy response from its national leadership. Within this policy void, many state governments are stepping up and taking action on adaptation planning. Yet we know little about why some states adopt State Adaptation Plans (SAPs), while others do not. This article investigates factors that predict the emergence of SAPs, both in terms of policy adoption and policy intensity (goal ambitiousness). Applying the diffusion of innovation theory, I consider the relative influence of internal state characteristics, regional pressures, and test for conditional effects between government ideologies and severity of the problem. The results show interesting differences between predictors that influence policy adoption and ambitiousness. States are more motivated to adopt a policy when faced with greater climate vulnerability, have more liberal citizenry, and where governments have crossed policy hurdles by previously passing mitigation plans. The intensity of policies and goal setting, moreover, is more likely to be driven by interest group politics and diffuse through policy learning or sharing information among neighboring states in Environmental Protection Agency regions. These findings support an emerging scholarship that uses more complex dependent variables in policy analysis. These variables have the potential to differentiate symbolic from substantive policies and capture finer information about predictors of importance.     

Applying Stone in a Western Landscape: Ranchers,Conservationists, and Causal Stories in the “American Serengeti”

As the emergence of nongovernmental conservation efforts generates conflict among various stakeholders, the causal story that each party articulates regarding conservation and the causes of land degradation reflects their unique interests. This study uses existing literature to evaluate causal stories surrounding a contemporary conservation effort: Montana's American Prairie Reserve. Through qualitative review of web‐based documents and newspaper articles, it generates a preliminary account of key stakeholders' causal stories. The case study suggests that parties who might be disadvantaged by ascribing responsibility for environmental harms in an adversarial fashion may instead elect to articulate causal stories that are more neutral than existing approaches might forecast. The study concludes by suggesting that further development of causal story literature may enable it to better address contemporary conservation efforts.     

A 21st Century Low‐Carbon Transition in U.S. Electric Power: Extent,Contributing Factors,and Implications

The U.S. electric power sector has experienced a substantial shift of the generation mix since the turn of the century, moving from heavy reliance on coal‐powered generation to one drawing more from natural gas and, more recently, renewables. This transition has been forged by a mix of macroeconomic factors (recession and recovery); technological breakthroughs (horizontal drilling coupled with hydraulic fracturing; improvements in natural gas plant efficiency); clean energy policies at federal, state, and local levels of government; and private sector demands for carbon‐free energy sources. These factors have combined to reduce carbon emissions from electric power generation substantially this century. In this article we examine the extent of this transition, its causes, as well as the distinct American institutional factors steering it, including energy and environmental federalism, electoral politics, and the political economy of clean energy policy enactment and resistance.     

我国公共政策失灵问题研究综述

政策失灵是世界各国共有的现象。我国学界主要从理论和实践两个方面分析了政策失灵的内涵、类型、成因、对策等,不断加深对政策失灵问题的认识。但目前政策失灵研究还存在基本概念界定不清、理论创新不足、视角较为狭窄、研究深度不够等问题。深化政策失灵研究,需要在学理上对其内涵进行清晰界定,构建政策失灵的分析模型;将政策失灵与政策过程相结合,将思辨分析与实证分析相结合,分析政策失灵的具体表现、内在机理、应对思路,增强政策失灵分析的中国特色和理论创新。     

Chemical Imaging of Human Fingermark by X-ray Photoelectron Spectroscopy (XPS)

X-ray photoelectron spectroscopy (XPS) is a widely used technique to characterize the surface chemistry of materials. It plays a crucial role in accessing qualitative and quantitative information and in detecting the presence of chemical functional groups on the surface of any material. The forensic methods available to detect and identify elements and organic/inorganic compounds are often destructive, so evidence cannot be re-analyzed. However, XPS allows rapid analysis of samples without damaging them. Recently, an increasing number of forensic researchers have begun to study certain chemical information on fingermarks. In this study, the authors aimed to present the applicability and power of XPS imaging in fingermark analysis which can also provide specific information about the fingermark chemical composition. Herein, monochromated X-ray (Al Kα) spot size was fixed at 50 μm. XPS mapping resulted in the acquisition of spectra at each pixel, in an array of 41 × 30 pixels with a step size of 50 μm. Then, a simple discussion has been made about how the scanned surface spectrum and basic snapshot spectra are used to identify different components at a fingertip of a scanned surface area (~3 mm²). Hence, a fingermark pattern contaminated with caffeine, TiO₂, and Pb/PbO deposited on the silicon wafer can be chemically mapped and visualized by XPS using principal component analysis (PCA). Thus, the present study showed the possible applicability of XPS for the identification of illicit drugs of abuse, gunshot residue, and skin care products on latent fingermark by mimicking a crime scene evidence.     

Distribution of the Minutiae in Hypothenar Palm Prints in Slovak Adults: Indications for Personal Identification

Minutiae are small distinguishing features found along every ridge flow, which make each friction ridge print unique. The most common friction ridge prints found at the crime scene are fingerprints; therefore, the most of the minutiae studies are focused exactly on this kind of prints. The authors believe that further examination and enlargement of the palm print database could result in better use of the palm prints for personal identification. We analyzed a total of 160 palm prints from 40 females and 40 males aged between 18 and 70 years from Slovakia. For the evaluation of the minutiae, the area of the hypothenar had to be marked out. The classification of the minutiae used for this study was based on a modified version of the classification system using the total of 13 types of minutiae. The frequency of every minutiae type was calculated and, using the chi-square test with Yates's correction, bilateral and sex differences were assessed. The relationship between the different types of minutiae was examined with Pearson's correlation test. During the initial phases of the identification process, the focus should be on the least common types of minutiae (Y or M and return), which were found not to correlate; thus, their mutual occurrence is random (e.g., overlap—Y or M, crossbar—return, or Y or M—dock). The results of the present study show which specific minutiae types are the most suitable for personal identification. These findings may be beneficial in more effective outcome of the identification process.     

Composite Machine Learning Algorithm for Material Sourcing,

This study developed a composite machine learning algorithm for attribution of materials of forensic interest (like ammonium nitrate) to original sources. k-nearest neighbor and random forest models were used for source elimination and classification, respectively, in a two-step, composite algorithm based on particle color, size/shape, and trace element concentration features. Novel approaches for simulation to supplement within-source reference features based on empirically measured multi-lot analyses, an improved hold-one-lot-out method for cross-validation, an assessment of the likelihood of the presence of a reference sample, fusion of the source probabilities from the respective classification models, and the calculation of metrics for assessing ensemble sourcing performance are described. Excellent sourcing predictions were obtained; the sourcing algorithm identified the correct source as the top choice 89% of the time, and the correct source was identified to be an average of 2.7 times more likely than the most likely incorrect source.