Does the Clean Air Action Really Affect Labor Demand in China?

How to balance resources, environment, and economic growth to achieve sustainable development is a challenge for developing countries. In 2013, China implemented a high-stringency environmental regulation—the Clean Air Action, which has effectively controlled air pollution. To explore the economic cost of environmental regulation, this paper investigates the policy effect on employment in the industrial sector. However, there are still controversies about whether environmental regulations impact employment. Based on the city-level data and firm-level data, this study applied a quasi-natural experiment for policy evaluation and used the mediating effect model for mechanism analysis. The difference-in-difference estimation results show that environmental regulation has a significant impact on employment. The mechanism analysis verifies that output adjustment, capital input, and green innovation are the main channels, by which environmental regulation distresses employment. The findings of this paper could be extended to other countries at a similar stage of development.

‘Trust Us’: Open Data and Preregistration in Political Science and International Relations

The scientific method is predicated on transparency -- yet the pace at which transparent research practices are being adopted by the scientific community is slow. The replication crisis in psychology showed that published findings employing statistical inference are threatened by undetected errors, data manipulation, and data falsification. To mitigate these problems and bolster research credibility, open data and preregistration have increasingly been adopted in the natural and social sciences. While many political science and international relations journals have committed to implementing these reforms, the extent of open science practices is unknown. We bring large-scale text analysis and machine learning classifiers to bear on the question. Using population-level data -- 93,931 articles across the top 160 political science and IR journals between 2010 and 2021 -- we find that approximately 21% of all statistical inference papers have open data, and 5% of all experiments are preregistered. Despite this shortfall, the example of leading journals in the field shows that change is feasible and can be effected quickly.

Examining the Association between Racialized Economic Threat and White Suicide in the United States, 2000–2016

Suicide is steadily rising. Many blamed worsening economic conditions for this trend. Sociological theory established clear pathways between joblessness and suicide focused on status threat, shame, and consequent disruption of social relationships. However, recent empirical research provides little support for a link between unemployment and suicide. I attempt to reconcile this contradiction by focusing on white suicide and white employment-to-population ratio. Whiteness is not just a default category but a pervasive ideology that amplifies the effects of status loss. The white employment-to-population ratio represents a form of racialized economic threat and accounts for discouraged workers who have exited the labor force. I use longitudinal hybrid models with U.S. state-level data, 2000 to 2016, and find that decreasing employment is associated with increasing suicide among the white population and white men. I discuss this study’s contributions to the literature on suicide and joblessness and the emerging scholarship on whiteness and health.

Resource frontiers and agglomeration economies: The varied logics of transnational land-based investing in Southern and Eastern Africa

Actor-level data on large-scale commercial agriculture in Sub-Saharan Africa are scarce. The peculiar choice of transnational investing in African land has, therefore, been subject to conjecture. Addressing this gap, we reconstructed the underlying logics of investment location choices in a Bayesian network, using firm- and actor-level interview and spatial data from 37 transnational agriculture and forestry investments across 121 sites in Mozambique, Zambia, Tanzania, and Ethiopia. We distinguish four investment locations across gradients of resource frontiers and agglomeration economies to derive the preferred locations of different investors with varied skillsets and market reach (i.e., track record). In contrast to newcomers, investors with extensive track records are more likely to expand the land use frontier, but they are also likely to survive the high transaction costs of the pre-commercial frontier. We highlight key comparative advantages of Southern and Eastern African frontiers and map the most probable categories of investment locations.

Seeing the Forest and Its Trees Together: Implementing 3D Light Microscopy Pipelines for Cell Type Mapping in the Mouse Brain

The brain is composed of diverse neuronal and non-neuronal cell types with complex regional connectivity patterns that create the anatomical infrastructure underlying cognition. Remarkable advances in neuroscience techniques enable labeling and imaging of these individual cell types and their interactions throughout intact mammalian brains at a cellular resolution allowing neuroscientists to examine microscopic details in macroscopic brain circuits. Nevertheless, implementing these tools is fraught with many technical and analytical challenges with a need for high-level data analysis. Here we review key technical considerations for implementing a brain mapping pipeline using the mouse brain as a primary model system. Specifically, we provide practical details for choosing methods including cell type specific labeling, sample preparation (e.g., tissue clearing), microscopy modalities, image processing, and data analysis (e.g., image registration to standard atlases). We also highlight the need to develop better 3D atlases with standardized anatomical labels and nomenclature across species and developmental time points to extend the mapping to other species including humans and to facilitate data sharing, confederation, and integrative analysis. In summary, this review provides key elements and currently available resources to consider while developing and implementing high-resolution mapping methods.

Low-carbon governance, fiscal decentralization and sulfur dioxide emissions: Evidence from a quasi-experiment with Chinese heavy pollution enterprises

This paper investigates the effects of enterprise environmental governance under low-carbon pilot policies in China with a difference in differences (DID) design. In examining the development of these policies, we focus on exploring their effects on sulfur dioxide emissions of heavily polluting enterprises based on prefectural city- and firm-level data from 2003-2014. Overall, the policies significantly increased enterprise SO2 emissions, and the underlying reason being that investments in CO2 control crowded out investment in SO2 control in enterprises in low-carbon pilot regions. We also find that the implementation of low-carbon pilot policies resulted in greater SO2 emissions from state-owned enterprises and enterprises in western regions than from non-state-owned enterprises and those in eastern regions. It is further found that fiscal decentralization and the associated mediating effect of market segmentation promote enterprises' CO2 control and inhibit their SO2 control. This study helps us re-examine the overall environmental effects of low-carbon policies and has implications for the revision and improvement of environmental governance policies in developing countries.

SARS-CoV-2 infection and COVID-19 vaccination rates in pregnant women in Scotland

Population-level data on COVID-19 vaccine uptake in pregnancy and SARS-CoV-2 infection outcomes are lacking. We describe COVID-19 vaccine uptake and SARS-CoV-2 infection in pregnant women in Scotland, using whole-population data from a national, prospective cohort. Between the start of a COVID-19 vaccine program in Scotland, on 8 December 2020 and 31 October 2021, 25,917 COVID-19 vaccinations were given to 18,457 pregnant women. Vaccine coverage was substantially lower in pregnant women than in the general female population of 18−44 years; 32.3% of women giving birth in October 2021 had two doses of vaccine compared to 77.4% in all women. The extended perinatal mortality rate for women who gave birth within 28 d of a COVID-19 diagnosis was 22.6 per 1,000 births (95% CI 12.9−38.5; pandemic background rate 5.6 per 1,000 births; 452 out of 80,456; 95% CI 5.1−6.2). Overall, 77.4% (3,833 out of 4,950; 95% CI 76.2−78.6) of SARS-CoV-2 infections, 90.9% (748 out of 823; 95% CI 88.7−92.7) of SARS-CoV-2 associated with hospital admission and 98% (102 out of 104; 95% CI 92.5−99.7) of SARS-CoV-2 associated with critical care admission, as well as all baby deaths, occurred in pregnant women who were unvaccinated at the time of COVID-19 diagnosis. Addressing low vaccine uptake rates in pregnant women is imperative to protect the health of women and babies in the ongoing pandemic.