LIVE AID REVISITED: LONG‐TERM IMPACTS OF THE 1984 ETHIOPIAN FAMINE ON CHILDREN

In 1984, the world was shocked at the scale of a famine in Ethiopia that caused over half a million deaths, making it one of the worst in recent history. The mortality impacts are clearly significant. But what of the survivors? This paper provides the first estimates of the long‐term impact of the famine 20 years later, on the height of young adults aged 19–22 years who experienced this severe shock as infants during the crisis. An innovative feature of the analysis is that famine intensity is measured at the household level, while impacts are assessed using a difference‐in‐differences comparison across siblings, and compared with an IV cross‐section, using rainfall as an instrument for the shock. We find that by adulthood, affected children who were aged of 12‐36 months at the peak of the crisis are significantly shorter than the older cohort, and their unaffected peers, by at least 5 cm. There are no significant effects on those in utero during the crisis, although we cannot rule out that for this cohort, the selection effect dominates scarring. Indicative calculations show that for the affected group such height loss may lead to income losses of around 5% per year over their lifetime. The evidence also suggests that the relief operations at the time made little difference to those who survived.     

The impact of incomplete geocoding on small area population estimates

Small-area population estimates are often made using geocoded address data in conjunction with the housing-unit method. Previous research, however, suggests that these data are subject to systematic incompleteness that biases estimates of race, ethnicity, and other important demographic characteristics. This incompleteness is driven largely by an inability to complete georeference address-based datasets. Given these challenges, small-area demographers need further, and to date largely unavailable, information on the amount of error typically introduced by using incompletely geocoded data to estimate population. More specifically, we argue that applied demographers should like to know if these errors are statistically significant, spatially patterned, or systematically related to specific population characteristics. This paper evaluates the impact of incomplete geocoding on accuracy in small-area population estimates, using a Vintage 2000 set of block-group estimates of the household population for the Albuquerque, NM metro area. Precise estimates of the impact of incomplete geocoding on the accuracy of estimates are made, associations with specific demographic characteristics are considered, and a simple potential remediation based on Horvitz-Thompson theory is presented. The implications of these results for the practice of applied demography are reviewed.     

And … action? Gender,knowledge and inequalities in the UK screen industries

This article explores how a knowledge ecology framework can help us better understand the production of gender knowledge, especially in relation to improving gender equality. Drawing on Law, Ruppert, and Savage, it analyses what knowledge of gender inequality is made visible and actionable in the case of the UK screen sector. We show: (i) that the gender knowledge production for the UK screen sector operated with reductionist understandings of gender and gender inequality, and presented gender inequality as something that needed evidencing rather than changing; and (ii) that gender knowledge was circulated in two relatively distinct circuits, a policy‐ and practice‐facing one focused on workforce statistics and a more heterogeneous and critical academic one. We then discuss which aspects of gender inequality in the UK screen industry remained invisible and thus less actionable. The article concludes with a critical appreciation of how the knowledge ecology framework might help better understand gender knowledge production, in relation to social change in the UK screen sector and beyond.     

Armor for Ethnographers

As its public readership has vastly increased, ethnography has entered a new world of social interaction, at once rewarding and dangerous. Among social researchers, ethnographic fieldworkers are unusually exposed to pressures to both make and break promises of confidentiality to subjects because they work to expose subjects to readers in a relatively transparent way. By showing individuals in their individuality, ethnographers draw the attention of nonacademic readers, which can be motivating but also terrifying because sources might be questioned and subjects sought out in ways the ethnographer may not be able to control. Tracking the schizophrenia that now threatens to pervade ethnographic work, I describe overlooked risks that all practitioners face and point to an as‐yet unexplored collective strategy for resisting pressures to breach promises of confidentiality. I then switch from a collective to an individual focus and review ethnography as a multiphased research act, suggesting ways to minimize personal and ethical risks at each stage.     

Stages do matter; and there are even more of them to consider

Shultziner and Goldberg are is correct to say we need to treat the various stages of social movement origins, protests, and outcomes separately, with detailed analysis of each stage. However, a triparte stage theory may be insufficient, as each stage can have diverse potential trajectories driven by distinct causal mechanisms. Social movement analysis should help us recognize the many points at which complex movement trajectories can be advanced or reversed, and how actions at each stage create reverberations in the wider society.     

The aging of the Chinese population and the cost of health care

It is projected that by 2050 China could have a staggering 115 million elderly citizens over 80 years old. Serious planning is needed to cope with this demand. This is the direct and inevitable result of the one-child policy that came into effect in 1979, as an independent policy to the Comprehensive Economic Reform; but the complementary nature is unmistakable.In accordance with the objective of this special issue of the Social Science Journal, the modest objective of this paper presents a brief history of the health care reform which really only began in 2002. We borrow from a major pilot study (the CHARLS data set) to provide quantitative measures of the cost of medical insurance. CHARLS samples two provinces, the inland poorer Gangsu and the coastal prosperous Zhejiang. The premium was 13 and 27 Yuan for the rural populations Gansu and Zhejiang. For the urban population, the premium was 289 versus 337 for men versus women in urban Gansu. But for the urban areas of Zhejiang, the pattern is radically different; 324.3 Yuan for women and a much higher 608 Yuan for men.Urban residents have always enjoyed better health care. With the support of the central government, 90% of rural population now received some form of basic health coverage. The issue is the reimbursement rate. For outpatient care, the reimbursement rates max out at under 40% and 32% for the urban and rural patients, respectively. This is certainly not enough to cover catastrophic illness, and that is why many Chinese feel they are just one major illness away from utter poverty. Outpatient care is even worse. The reimbursement rates average around only 10%. As Chinese statistics on full medical cost (especially for the elderly) is lacking, we utilize statistics from Taiwan and try to estimate the health care cost of the aging population.We discuss potential issues observed in the Taiwan experience, and proposed an incentive scheme, Self-Motivated Health Maintenance (SMHM), to deal with moral hazards and to reduce the overall health care cost. We believe the SMHM is a win–win–win solution. China has the possibility of building this into their health insurance.     

How does the DerSimonian and Laird procedure for random effects meta-analysis compare with its more efficient but harder to compute counterparts?

The procedure suggested by DerSimonian and Laird is the simplest and most commonly used method for fitting the random effects model for meta-analysis. Here it is shown that, unless all studies are of similar size, this is inefficient when estimating the between-study variance, but is remarkably efficient when estimating the treatment effect. If formal inference is restricted to statements about the treatment effect, and the sample size is large, there is little point in implementing more sophisticated methodology. However, it is further demonstrated, for a simple special case, that use of the profile likelihood results in actual coverage probabilities for 95% confidence intervals that are closer to nominal levels for smaller sample sizes. Alternative methods for making inferences for the treatment effect may therefore be preferable if the sample size is small, but the DerSimonian and Laird procedure retains its usefulness for larger samples.