改造我们的教学

进入"双高时代",我们距离新时代高等职业教育"舞龙头"的教学还有问题和"短板",应该改造教学方法和学习与研究制度。在剖析改造教学原因的基础上,厘清看待教学中存在问题的两种互相对立的态度,提出改造教学的革故鼎新路径,如强化"课堂教学为王"的意识,强化学习与专业研究,强化教学的职业素养,强化教师的课堂教学治理。     

Personal Income Tax Reform in China in 2018 and Its Impact on Income Distribution

In the context of personal income tax (PIT) reform in China in 2018, this paper examines some of the major issues of concern regarding the reform and income distribution. Using the China Personal Income Tax Micro‐simulation model, the paper compares the differences between the 2011 and 2018 PIT systems, and finds that residents relying on different income sources may face a large degree of real tax rate change. Once the tax system is altered to PIT 2018, the coverage of PIT for wage earners will decrease from 46.9 to 23.4 percent, the income redistributive effect will drop from 1.95 to 1.22 percent and the PIT's role in fiscal revenue will also be negatively affected. Nevertheless, if individual income continues to grow, the share of PIT in fiscal revenue is expected to return to the 2018 level in 2022, but its income redistribution function is difficult to recover in the short term. The paper finds that the effect of PIT on income distribution depends on the tax structure. Gradual transition to an “entirely comprehensive” tax system when conditions are appropriate will achieve better income redistribution results at a lower average tax rate.     

Class formation and commodity chains in the making of regional monocultures: Agrarian reform from above and below in Mexico's henequen and cotton zones

This paper analyses the rise and fall of two regional monocultures in Mexico: the henequen zone in the southern state of Yucatán and the cotton‐growing area of La Laguna. Both regions experienced a dramatic expansion of commodity production between 1870 and 1910, but their key crops came to be cultivated under different labour regimes: debt peonage in the case of henequen and wage labour in the case of cotton. The process of class formation that unfolded in each region culminated in the 1930s in different kinds of crises. In Yucatán, a political struggle between hacienda owners and the federal government resulted in an agrarian reform “from above.” In La Laguna, class conflict between rural wageworkers and the landed bourgeoisie forced an agrarian reform “from below.” These previously distinct labour regimes converged in subsequent decades, however, as rural producers became de facto wageworkers on state‐organized and state‐administered production units known as collective ejidos. Ultimately, changes in the global markets for cotton and henequen, combined with the inability of the Mexican state to reconcile the political logic of agrarian clientelism with shifting commodity chain dynamics, resulted in the collapse of these regional monocultures in the late 20th century.     

Material weakness disclosures and restatement announcements: The joint and order effects

We examine differences in stock price, option volatility, and litigation reactions to restatement announcements that are associated with a material weakness (MW) disclosure. Contrasted with restatements that are not associated with any MW disclosure, our analyses reveal that firms that announce both a restatement and an associated MW experience significantly more negative market returns, greater implied volatility, and higher likelihood of class action lawsuits. Separating the restatements into timely reporters, where the MW precedes the restatement, and non‐timely reporters, where the MW is concurrent with or follows the restatement, we find that timely reporters experience more negative returns at the time of the restatement, relative to non‐timely reporters, suggesting that investors perceive the early MW disclosure to signal more pervasive control‐related problems. Interestingly, we find that timely and non‐timely reporters are equally likely to be sued, consistent with the argument that wrongdoing (through either a timely or non‐timely MW disclosure) provides stronger grounds for establishing scienter. However, timely reporters appear to secure more favorable litigation outcomes: they face higher likelihood of lawsuit dismissals and pay much lower settlements, compared to non‐timely reporters. Overall, our evidence provides new insights into how market participants incorporate information about internal control weaknesses into their perceptions regarding the economic implications of financial restatements, and financial reporting quality.     

Being Good Parents or Being Good Citizens: Dilemmas and Contradictions of Urban Families in Middle‐Class Enclaves and Mixed Neighbourhoods in Germany

In recent years, cities have become ever more attractive to middle‐class families. On the one hand, middle‐class families tend to withdraw into (often newly built) socially homogeneous middle‐class neighbourhoods. On the other hand, they are also known to move into inner‐city and socially mixed areas, thus triggering processes of gentrification. Academic literature has often denounced these housing choices as being either ‘separatist’ or ‘revanchist’, more broadly categorized as strategies of ‘middle‐class disaffiliation’. Although there is a grain of truth in these interpretations, the reality is certainly more complicated. In our research on middle‐class parents’ housing and neighbourhood choices as well as their patterns of neighbourhood use, carried out in each of the two types of residential area mentioned above, we have only very rarely found an explicit desire to draw boundaries that exclude those ‘beneath’ them. We rather argue that the housing choices and neighbourhood‐related activities of middle‐class family households are heavily influenced by the specific dilemmas the interviewees face as (working) urban parents. While a significant number of respondents worry about the social sustainability, justice and cohesion of urban society, they are also concerned about the future prospects of their children. Many find it difficult to reconcile these conflicting normative demands under the prevailing circumstances.     

Recognition in India’s new service professions: gym trainers and coffee baristas

ABSTRACT

How do employees in “new services”, such as coffee baristas and gym trainers in India, see their jobs? In this paper, we build on extensive fieldwork in gyms and coffee chains that cater to the emerging Indian middle classes. Our research highlights the importance of respect and recognition in making service interactions more meaningful for new service workers. Generally hailing from the lower middle classes, new service work offers important opportunities to interact with and learn from English-speaking upper middle-class customers and clients. Besides the opportunity to interact and learn, the acknowledgement they receive for their skills and (bodily) accomplishments make such professions attractive as well. Even if this holds the potential for upward socioeconomic mobility, our findings also point at the resilience of social hierarchies. Drawing on literature on service interactions and new middle-class formation in India, this paper provides important insight into how young Indians navigate and negotiate the opportunities and pitfalls that come with the country's changing socioeconomic landscape.     

The financial advice puzzle: The role of consumer heterogeneity in the advisor choice

We investigate motivational drivers of financial advisor use, accounting for investor heterogeneity, with the goal of helping institutions increase the use of financial advisor services. The results from a latent class choice model reveal two distinct segments that differ in their approach to the financial advice decision. While higher levels of risk tolerance, trust, and self-efficacy increase financial advice use for both segments, albeit at much higher propensities for Segment 1, personality only matters for Segment 1. Moreover, their regulatory focus differs with Segment 1 being promotion and Segment 2 being prevention focused. Using these results, we offer suggestions for marketing strategies.     

浅析区块链技术对小微企业信用认证及融资的作用

随着经济社会的全面发展,经济全球化已经成为全新的发展趋势,紧随其后的是后金融危机时代的到来。区块链是一种特定的数据技术,它在安全和便捷方面一直被业内人士所看好。论文围绕区块链技术对小微企业信用认证及融资的作用展开讨论分析,通过讨论分析有助于实现小微企业成功融资,为我国小微企业提供强有力的保障与支撑。     

Food values and heterogeneous consumer responses to nanotechnology

Agricultural applications of nanotechnology are at a relatively early stage and little is known about consumer responses to the technology. Canadian consumer responses to food nanotechnology are examined through the lens of the Food Value Scale. Data from a survey of Canadian consumers are used to evaluate the relative importance of eleven food values to food purchase decisions. We find that taste, safety, nutrition, and price are among the most important food values to Canadians, however, consumers exhibit considerable heterogeneity with respect to the priority placed on these values. A discrete choice experiment (DCE) explores the effect of food values on choice behavior. The DCE is positioned as a sliced apple product with non-browning and antioxidant-enhanced features introduced through the use of nanocoating or a conventional coating method. Random parameters logit (RPL) and latent class models (LCM) confirm the existence of significant preference heterogeneity. The LCM identifies three classes of consumers: “supporters,” “doubters,” and “opponents” who differ in their reaction to nanotechnology and in the relative importance placed on food values such as naturalness, novelty, and convenience. The analysis shows that food values provide additional insights into consumers’ food choices and their attitudes toward novel food technologies.     

A machine-learning method for improving crash injury severity analysis: a case study of work zone crashes in Cairo,Egypt

Abstract

The quality of vehicular collision data is crucial for studying the relationship between injury severity and collision factors. Misclassified injury severity data in the crash dataset, however, may cause inaccurate parameter estimates and consequently lead to biased conclusions and poorly designed countermeasures. This is particularly true for imbalanced data where the number of samples in one class far outnumber the other. To improve the classification performance of the injury severity, the paper presents a robust noise filtering technique to deal with the mislabels in the imbalanced crash dataset using the advanced machine learning algorithms. We examine the state-of-the-art filtering algorithms, including Iterative Noise Filtering based on the Fusion of Classifiers (INFFC), Iterative Partitioning Filter (IPF), and Saturation Filter (SatF). In the case study of Cairo (Egypt), the empirical results show that: (1) the mislabels in crash data significantly influence the injury severity predictions, and (2) the proposed M-IPF filter outperforms its counterparts in terms of the effectiveness and efficiency in eliminating the mislabels in crash data. The test results demonstrate the efficacy of the M-IPF in handling the data noise and mitigating the impacts thereof.