网络民族志基于研究者身份的伦理关系

民族志一度是研究者专业生产他者知识的手段与途径,但在反思传统与顺应新潮流——互联网的基础上,我们发现,一直以来研究者自己也是民族志的研究对象,互联网兴起之后,这种倾向更加明显.网络时代的到来促使研究者的身份发生了显著转变:由自己是主体,被研究者是他者,转变为双方是平等的交互主体;由认识主体转变为实践主体;由主动的实践者转变为静默的潜伏者等.网络民族志中研究者身份的变化,为新的研究伦理关系的出现开辟了道路,即研究者与被研究者既是学术研究的手段,也是学术研究的目的.     

汉代乐舞中的人本主义精神探析

在我国长达3000多年的乐舞文化中,汉代乐舞以其张扬阔大、发扬蹈厉的强悍风格独树一帜,堪称中华乐舞史的最强音.造就强汉之音的精神底座,是在秦汉代际蓬勃兴起的人本主义精神.从汉武时期乐制的更作和乐府制度的确立,到盛行两汉的乐舞形制,再到志尽于诗、音尽于曲的乐舞歌诗和意气相尚、悲歌厉响的审美取向,无不反映并凸显着人本主义精神的光辉.在我国当下民族复兴的进程中,人本主义精神同样应成为时代诉求.     

中国“碳中和”目标的实现路径与模式选择

围绕中国碳中和目标的实现路径与模式选择问题，提出了一个中国应对气候变化整体治理模式，即多阶段混合主导型碳中和实现模式。这一模式是以国家为核心，在一定时期和内外环境约束下，通过减排和增汇路径，对中国境内由人类活动造成的CO2排放与人为CO2吸收量之间关系进行调整和平衡的过程；其内部由宏观、中观和微观三层结构组成，每层结构各不相同。多阶段混合主导型碳中和实现模式的提出，拓展和完善了气候变化整体治理理论，为气候变化治理提供了机制借鉴。     

随机需求环境下联产品系统价格与产量决策研究

基于固定比例生产技术和多产品随机需求的情形,研究了联产品制造商的两阶段产量和价格联合优化模型。通过反向倒推的优化求解,得到了联产品制造商的最优产量和价格决策以及变化规律。同时研究了需求服从均匀分布时,需求波动对均衡的影响。研究结果表明,在订货成本较低和一种产品的需求波动性较大时,当另外一种产品的波动增大,则该产品的最优订货量增大,同时价格下降。借助数值仿真,分析了价格敏感度和产出比例对最优决策和利润的影响。结果表明,在给定一种产品的价格敏感度时,另外一种的价格敏感度越大,那么该产品的价格就越低,制造商的订货量就下降。当一种产品的产出比例固定时,另一种产品的产出比例上升时,则该产品的价格下降,制造商的订货量下降,总利润上升。     

Integrating Operational and Organizational Aspects in Interdependent Infrastructure Network Recovery

Managing risk in infrastructure systems implies dealing with interdependent physical networks and their relationships with the natural and societal contexts. Computational tools are often used to support operational decisions aimed at improving resilience, whereas economics‐related tools tend to be used to address broader societal and policy issues in infrastructure management. We propose an optimization‐based framework for infrastructure resilience analysis that incorporates organizational and socioeconomic aspects into operational problems, allowing to understand relationships between decisions at the policy level (e.g., regulation) and the technical level (e.g., optimal infrastructure restoration). We focus on three issues that arise when integrating such levels. First, optimal restoration strategies driven by financial and operational factors evolve differently compared to those driven by socioeconomic and humanitarian factors. Second, regulatory aspects have a significant impact on recovery dynamics (e.g., effective recovery is most challenging in societies with weak institutions and regulation, where individual interests may compromise societal well‐being). And third, the decision space (i.e., available actions) in postdisaster phases is strongly determined by predisaster decisions (e.g., resource allocation). The proposed optimization framework addresses these issues by using: (1) parametric analyses to test the influence of operational and socioeconomic factors on optimization outcomes, (2) regulatory constraints to model and assess the cost and benefit (for a variety of actors) of enforcing specific policy‐related conditions for the recovery process, and (3) sensitivity analyses to capture the effect of predisaster decisions on recovery. We illustrate our methodology with an example regarding the recovery of interdependent water, power, and gas networks in Shelby County, TN (USA), with exposure to natural hazards.     

Cross‐Sectional Psychological and Demographic Associations of Zika Knowledge and Conspiracy Beliefs Before and After Local Zika Transmission

Perceptions of infectious diseases are important predictors of whether people engage in disease‐specific preventive behaviors. Having accurate beliefs about a given infectious disease has been found to be a necessary condition for engaging in appropriate preventive behaviors during an infectious disease outbreak, while endorsing conspiracy beliefs can inhibit preventive behaviors. Despite their seemingly opposing natures, knowledge and conspiracy beliefs may share some of the same psychological motivations, including a relationship with perceived risk and self‐efficacy (i.e., control). The 2015–2016 Zika epidemic provided an opportunity to explore this. The current research provides some exploratory tests of this topic derived from two studies with similar measures, but different primary outcomes: one study that included knowledge of Zika as a key outcome and one that included conspiracy beliefs about Zika as a key outcome. Both studies involved cross‐sectional data collections that occurred during the same two periods of the Zika outbreak: one data collection prior to the first cases of local Zika transmission in the United States (March–May 2016) and one just after the first cases of local transmission (July–August). Using ordinal logistic and linear regression analyses of data from two time points in both studies, the authors show an increase in relationship strength between greater perceived risk and self‐efficacy with both increased knowledge and increased conspiracy beliefs after local Zika transmission in the United States. Although these results highlight that similar psychological motivations may lead to Zika knowledge and conspiracy beliefs, there was a divergence in demographic association.     

试述新中国成立初期中共干部的专业教育

新中国成立初期,中国共产党专业干部队伍基础十分薄弱,不仅数量少,总体质量也不高,成为国家发展建设中的巨大瓶颈。为此,中国共产党迅速采取措施,大力加强专业干部队伍建设,其重要举措之一是广泛开展干部的专业教育。这一时期干部专业教育主要通过三种途径:创办专业干部学校、紧紧依托高等院校、举办各种专业讲座和短期培训班等。由于党和人民政府高度重视、精心组织和大力推动,干部专业教育取得了显著成效,不仅迅速提高了广大干部的专业水平和业务能力,满足国家发展建设的需要,并且对中共干部队伍建设产生了深远影响。     

Towards Uniformly Efficient Trend Estimation Under Weak/Strong Correlation and Non‐stationary Volatility

In this paper, we consider the deterministic trend model where the error process is allowed to be weakly or strongly correlated and subject to non‐stationary volatility. Extant estimators of the trend coefficient are analysed. We find that under heteroskedasticity, the Cochrane–Orcutt‐type estimator (with some initial condition) could be less efficient than Ordinary Least Squares (OLS) when the process is highly persistent, whereas it is asymptotically equivalent to OLS when the process is less persistent. An efficient non‐parametrically weighted Cochrane–Orcutt‐type estimator is then proposed. The efficiency is uniform over weak or strong serial correlation and non‐stationary volatility of unknown form. The feasible estimator relies on non‐parametric estimation of the volatility function, and the asymptotic theory is provided. We use the data‐dependent smoothing bandwidth that can automatically adjust for the strength of non‐stationarity in volatilities. The implementation does not require pretesting persistence of the process or specification of non‐stationary volatility. Finite‐sample evaluation via simulations and an empirical application demonstrates the good performance of proposed estimators.     

Feminized Forestry: The Promises and Pitfalls of Change in a Masculine Organization

The gendering of forestry as a distinctly masculine profession has led to a wide range of negative outcomes, including legal actions concerning discrimination, poor public perceptions and poor environmental records. Forestry organizations have addressed these concerns by attempting to increase the number of women in the profession. These efforts have been largely ineffective. Using the case of community‐based forestry, I argue that when we begin to consider not only women but also normatively feminine values as agents of change, our understanding of the profession of forestry may be rejuvenated.