Results for “zmp”
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The demise of the happy two-parent family

Here is new work by Rachel Sheffield and Scott Winship, I will not impose further indentation:

“-          We argue, against conventional wisdom on the right, that the decades of research on the effects of single parenthood on children amounts to fairly weak evidence that kids would do better if their actual parents got or stayed married. That is not to say that that we think single parenthood isn’t important–it’s a claim about how persuasive we ought to find the research on a question that is extremely difficult to answer persuasively. But even if it’s hard to determine whether kids would do better if their unhappy parents stay together, it is close to self-evident (and uncontroversial?) that kids do better being raised by two parents, happily married.

–          We spend some time exploring the question of whether men have become less “marriageable” over time. We argue that the case they have is also weak. The pay of young men fell over the 1970s, 1980s, and early 1990s. But it has fully recovered since. You can come up with other criteria for marriageability–and we show several trends using different criteria–but the story has to be more complicated to work. Plus, if cultural change has caused men to feel less pressure to provide for their kids, then we’d expect that to CAUSE worse outcomes in the labor market for men over time. The direction of causality could go the other way.

–          Rather than economic problems causing the increase in family instability, we argue that rising affluence is a better explanation. Our story is about declining co-dependence, increasing individualism and self-fulfillment, technological advances, expanded opportunities, and the loosening of moral constraints. We discuss the paradox that associational and family life has been more resilient among the more affluent. It’s an argument we advance admittedly speculatively, but it has the virtue of being a consistent explanation for broader associational declines too. We hope it inspires research hypotheses that will garner the kind of attention that marriageability has received.

–          The explanation section closes with a look at whether the expansion of the federal safety net has affected family instability. We acknowledge that the research on select safety net program generosity doesn’t really support a link. But we also show that focusing on this or that program (typically AFDC or TANF) misses the forest. We present new estimates showing that the increase in safety net generosity has been on the same order of magnitude as the increase in nonmarital birth rates.

–          Finally, we describe a variety of policy approaches to address the increase in family stability. These fall into four broad buckets: messaging, social programs, financial incentives, and other approaches. We discuss 16 and Pregnant, marriage promotion programs, marriage penalties, safety net reforms, child support enforcement, Career Academies, and other ideas. We try to be hard-headed about the evidence for these proposals, which often is not encouraging. But the issue is so important that policymakers should keep trying to find effective solutions.”

A highly qualified reader emails me on heterogeneity

I won’t indent further, all the rest is from the reader:

“Some thoughts on your heterogeneity post. I agree this is still bafflingly under-discussed in “the discourse” & people are grasping onto policy arguments but ignoring the medical/bio aspects since ignorance of those is higher.

Nobody knows the answer right now, obviously, but I did want to call out two hypotheses that remain underrated:

1) Genetic variation

This means variation in the genetics of people (not the virus). We already know that (a) mutation in single genes can lead to extreme susceptibility to other infections, e.g Epstein–Barr (usually harmless but sometimes severe), tuberculosis; (b) mutation in many genes can cause disease susceptibility to vary — diabetes (WHO link), heart disease are two examples, which is why when you go to the doctor you are asked if you have a family history of these.

It is unlikely that COVID was type (a), but it’s quite likely that COVID is type (b). In other words, I expect that there are a certain set of genes which (if you have the “wrong” variants) pre-dispose you to have a severe case of COVID, another set of genes which (if you have the “wrong” variants) predispose you to have a mild case, and if you’re lucky enough to have the right variants of these you are most likely going to get a mild or asymptomatic case.

There has been some good preliminary work on this which was also under-discussed:

You will note that the majority of doctors/nurses who died of COVID in the UK were South Asian. This is quite striking. https://www.nytimes.com/2020/04/08/world/europe/coronavirus-doctors-immigrants.html — Goldacre et al’s excellent paper also found this on a broader scale (https://www.medrxiv.org/content/10.1101/2020.05.06.20092999v1). From a probability point of view, this alone should make one suspect a genetic component.

There is plenty of other anecdotal evidence to suggest that this hypothesis is likely as well (e.g. entire families all getting severe cases of the disease suggesting a genetic component), happy to elaborate more but you get the idea.

Why don’t we know the answer yet? We unfortunately don’t have a great answer yet for lack of sufficient data, i.e. you need a dataset that has patient clinical outcomes + sequenced genomes, for a significant number of patients; with this dataset, you could then correlate the presences of genes {a,b,c} with severe disease outcomes and draw some tentative conclusions. These are known as GWAS studies (genome wide association study) as you probably know.

The dataset needs to be global in order to be representative. No such dataset exists, because of the healthcare data-sharing problem.

2) Strain

It’s now mostly accepted that there are two “strains” of COVID, that the second arose in late January and contains a spike protein variant that wasn’t present in the original ancestral strain, and that this new strain (“D614G”) now represents ~97% of new isolates. The Sabeti lab (Harvard) paper from a couple of days ago is a good summary of the evidence. https://www.biorxiv.org/content/10.1101/2020.07.04.187757v1 — note that in cell cultures it is 3-9x more infective than the ancestral strain. Unlikely to be that big of a difference in humans for various reasons, but still striking/interesting.

Almost nobody was talking about this for months, and only recently was there any mainstream coverage of this. You’ve already covered it, so I won’t belabor the point.

So could this explain Asia/hetereogeneities? We don’t know the answer, and indeed it is extremely hard to figure out the answer (because as you note each country had different policies, chance plays a role, there are simply too many factors overall).

I will, however, note that this the distribution of each strain by geography is very easy to look up, and the results are at least suggestive:

  • Visit Nextstrain (Trevor Bedford’s project)
  • Select the most significant variant locus on the spike protein (614)
  • This gives you a global map of the balance between the more infective variant (G) and the less infective one (D) https://nextstrain.org/ncov/global?c=gt-S_614
  • The “G” strain has grown and dominated global cases everywhere, suggesting that it really is more infective
  • A cursory look here suggests that East Asia mostly has the less infective strain (in blue) whereas rest of the world is dominated by the more infective strain:
  • image.png

– Compare Western Europe, dominated by the “yellow” (more infective) strain: