Kathryn Paige Harden Profile in The New Yorker (Behavior Genetics)

This is a good profile of behavior geneticist Paige Harden (UT Austin professor of psychology, former student of Eric Turkheimer), with a balanced discussion of polygenic prediction of cognitive traits and the culture war context in which it (unfortunately) exists.

Can Progressives Be Convinced That Genetics Matters? 

The behavior geneticist Kathryn Paige Harden is waging a two-front campaign: on her left are those who assume that genes are irrelevant, on her right those who insist that they’re everything. 

Gideon Lewis-Kraus

Gideon Lewis-Kraus is a talented writer who also wrote a very nice article on the NYTimes / Slate Star Codex hysteria last summer.

Some references related to the New Yorker profile:

1. The paper Harden was attacked for sharing while a visiting scholar at the Russell Sage Foundation: Game Over: Genomic Prediction of Social Mobility 

2. Harden's paper on polygenic scores and mathematics progression in high school: Genomic prediction of student flow through high school math curriculum 

3. Vox article; Turkheimer and Harden drawn into debate including Charles Murray and Sam Harris: Scientific Consensus on Cognitive Ability?

A recent talk by Harden, based on her forthcoming book The Genetic Lottery: Why DNA Matters for Social Equality

Regarding polygenic prediction of complex traits 

I first met Eric Turkheimer in person (we had corresponded online prior to that) at the Behavior Genetics Association annual meeting in 2012, which was back to back with the International Conference on Quantitative Genetics, both held in Edinburgh that year (photos and slides [1] [2] [3]). I was completely new to the field but they allowed me to give a keynote presentation (if memory serves, together with Peter Visscher). Harden may have been at the meeting but I don't recall whether we met. 

At the time, people were still doing underpowered candidate gene studies (there were many talks on this at BGA although fewer at ICQG) and struggling to understand GCTA (Visscher group's work showing one can estimate heritability from modestly large GWAS datasets, results consistent with earlier twins and adoption work). Consequently a theoretical physicist talking about genomic prediction using AI/ML and a million genomes seemed like an alien time traveler from the future. Indeed, I was.

My talk is largely summarized here:

On the genetic architecture of intelligence and other quantitative traits 

https://arxiv.org/abs/1408.3421 

How do genes affect cognitive ability or other human quantitative traits such as height or disease risk? Progress on this challenging question is likely to be significant in the near future. I begin with a brief review of psychometric measurements of intelligence, introducing the idea of a "general factor" or g score. The main results concern the stability, validity (predictive power), and heritability of adult g. The largest component of genetic variance for both height and intelligence is additive (linear), leading to important simplifications in predictive modeling and statistical estimation. Due mainly to the rapidly decreasing cost of genotyping, it is possible that within the coming decade researchers will identify loci which account for a significant fraction of total g variation. In the case of height analogous efforts are well under way. I describe some unpublished results concerning the genetic architecture of height and cognitive ability, which suggest that roughly 10k moderately rare causal variants of mostly negative effect are responsible for normal population variation. Using results from Compressed Sensing (L1-penalized regression), I estimate the statistical power required to characterize both linear and nonlinear models for quantitative traits. The main unknown parameter s (sparsity) is the number of loci which account for the bulk of the genetic variation. The required sample size is of order 100s, or roughly a million in the case of cognitive ability.

The predictions in my 2012 BGA talk and in the 2014 review article above have mostly been validated. Research advances often pass through the following phases of reaction from the scientific community:

1. It's wrong ("genes don't affect intelligence! anyway too complex to figure out... we hope")

2. It's trivial ("ofc with lots of data you can do anything... knew it all along")

3. I did it first ("please cite my important paper on this")

Or, as sometimes attributed to Gandhi: "First they ignore you, then they laugh at you, then they fight you, then you win.”

See also To Predict the Future it is useful to understand the Past.

Technical note: 

In 2014 I estimated that ~1 million genotype | phenotype pairs would be enough to capture most of the common SNP heritability for height and cognitive ability. This was accomplished for height in 2017. However, the sample size of well-phenotyped individuals is much smaller for cognitive ability, even in 2021, than for height in 2017. For example, in UK Biobank the cognitive test is very brief (~5 minutes IIRC, a dozen or so questions), but it has not even been administered to the full cohort as yet. In the Educational Attainment studies the phenotype EA is only moderately correlated (~0.3 ?) or so with actual cognitive ability.

Hence, although the most recent EA4 results use 3 million individuals [1], and produce a predictor which correlates ~0.4 with actual EA, the statistical power available is still less than what I predicted would be required to train a really good cognitive ability predictor.

In our 2017 height paper, which also briefly discussed bone density and cognitive ability prediction, we built a cognitve ability predictor roughly as powerful as EA3 using only ~100k individuals with the noisy UKB test data. So I remain confident that  ~million individuals with good cognitive scores (e.g., SAT, AFQT, full IQ test) would deliver results far beyond what we currently have available. We also found that our predictor, built using actual (albeit noisy) cognitive scores exhibits less power reduction in within-family (sibling) analyses compared to EA. So there is evidence that (no surprise) EA is more influenced by environmental factors, including so-called genetic nurture effects, than is cognitive ability.

A predictor which captures most of the common SNP heritability for cognitive ability might correlate ~0.5 or 0.6 with actual ability. Applications of this predictor in, e.g., studies of social mobility or educational success or even longevity using existing datasets would be extremely dramatic.

James Oakes on What’s Wrong with The 1619 Project - Manifold Podcast #46

Steve and Corey talk to James Oakes, Distinguished Professor of History and Graduate School Humanities Professor at the Graduate Center of the City University of New York, about "The 1619 Project" developed by The New York Times Magazine. The project argues that slavery was the defining event of US history. Jim argues that slavery was actually the least exceptional feature of the US and that what makes the US exceptional is that it is where abolition first begins. Steve wonders about the views of Thomas Jefferson who wrote that “all men are created equal” but still held slaves. Jim maintains many founders were hypocrites, but Jefferson believed what he wrote.

Topics: Northern power, Industrialization, Capitalism, Lincoln, Inequality, Cotton, Labor, Civil War, Racism/Antiracism, Black Ownership.

Transcript

James Oakes (Bio)

Oakes and Colleagues Letter to the NYT and the Editor’s Response

The Fight Over the 1619 Project Is Not About the Facts

The World Socialist Web Site interview with James Oakes


man·i·fold /ˈmanəˌfōld/ many and various.

In mathematics, a manifold is a topological space that locally resembles Euclidean space near each point.

Steve Hsu and Corey Washington have been friends for almost 30 years, and between them hold PhDs in Neuroscience, Philosophy, and Theoretical Physics. Join them for wide ranging and unfiltered conversations with leading writers, scientists, technologists, academics, entrepreneurs, investors, and more.

Steve Hsu is VP for Research and Professor of Theoretical Physics at Michigan State University. He is also a researcher in computational genomics and founder of several Silicon Valley startups, ranging from information security to biotech. Educated at Caltech and Berkeley, he was a Harvard Junior Fellow and held faculty positions at Yale and the University of Oregon before joining MSU.

Corey Washington is Director of Analytics in the Office of Research and Innovation at Michigan State University. He was educated at Amherst College and MIT before receiving a PhD in Philosophy from Stanford and a PhD in a Neuroscience from Columbia. He held faculty positions at the University Washington and the University of Maryland. Prior to MSU, Corey worked as a biotech consultant and is founder of a medical diagnostics startup.

NYTimes Op-Ed from the future (Ted Chiang): Genetics and Cognitive Enhancement

In this scenario Ted Chiang forecasts that recipients of government-funded genetic enhancement will not catch up to children of elites who receive similar enhancements. The latter are born to rich, highly educated parents and have access to elite social networks, better schools, etc. The system is still not entirely fair (i.e., invariant to accidents of birth), because many non-genetic advantages still exist. But can we ever achieve equality of outcome? At what cost?

Nevertheless, perhaps the beneficiaries of the Gene Equality Project are at least better off than their siblings who were not in the program?

It is interesting that the Times is already flirting with the idea of redistribution of genetic endowments. See also The Neanderthal Problem.

NYTIMES OP-ED FROM THE FUTURE

It’s 2059, and the Rich Kids Are Still Winning
DNA tweaks won’t fix our problems.

Ted Chiang is an award-winning science fiction writer.

Editors’ note: This is the first installment in a new series, “Op-Eds From the Future,” in which science fiction authors, futurists, philosophers and scientists write op-eds that they imagine we might read 10, 20 or even 100 years in the future.

Last week, The Times published an article about the long-term results of the Gene Equality Project, the philanthropic effort to bring genetic cognitive enhancements to low-income communities. The results were largely disappointing: While most of the children born of the project have now graduated from a four-year college, few attended elite universities and even fewer have found jobs with good salaries or opportunities for advancement. With the results in hand, it is time for us to re-examine the efficacy and desirability of genetic engineering.

The intentions behind the Gene Equality Project were good. Therapeutic genetic interventions, such as correcting the genes that cause cystic fibrosis and Huntington’s disease, have been covered by Medicare ever since their approval by the Food and Drug Administration, making them available to the children of low-income parents. However, augmentations like cognitive enhancements have never been covered — not even by private insurance — and were available only to affluent parents. Amid fears that we were witnessing the creation of a caste system based on genetic differences, the Gene Equality Project was begun 25 years ago, enabling 500 pairs of low-income parents to increase the intelligence of their children.

The project offered a common cognitive-enhancement protocol involving modifications to 80 genes associated with intelligence. Each individual modification had only a small effect on intelligence, but in combination they typically gave a child an I.Q. of 130, putting the child in the top 5 percent of the population. This protocol has become one of the most popular enhancements purchased by affluent parents, and it is often referenced in media profiles of the “New Elite,” the genetically engineered young people who are increasingly prevalent in management positions of corporate America today. Yet the 500 subjects of the Gene Equality Project are not enjoying career success that is remotely comparable to the success of the New Elite, despite having received the same protocol.

A range of explanations has been offered for the project’s results. White supremacist groups have claimed that its failure shows that certain races are incapable of being improved, given that many — although by no means all — of the beneficiaries of the project were people of color. Conspiracy theorists have accused the participating geneticists of malfeasance, claiming that they pursued a secret agenda to withhold genetic enhancements from the lower classes. But these explanations are unnecessary when one realizes the fundamental mistake underlying the Gene Equality Project: Cognitive enhancements are useful only when you live in a society that rewards ability, and the United States isn’t one.

It has long been known that a person’s ZIP code is an excellent predictor of lifetime income, educational success and health. Yet we continue to ignore this because it runs counter to one of the founding myths of this nation: that anyone who is smart and hardworking can get ahead. Our lack of hereditary titles has made it easy for people to dismiss the importance of family wealth and claim that everyone who is successful has earned it. The fact that affluent parents believe that genetic enhancements will improve their children’s prospects is a sign of this: They believe that ability will lead to success because they assume that their own success was a result of their ability.

For those who assume that the New Elite are ascending the corporate ladder purely on the basis of merit, consider that many of them are in leadership positions, but I.Q. has historically had only a weak correlation with effectiveness as a leader. Also consider that genetic height enhancement is frequently purchased by affluent parents, and the tendency to view taller individuals as more capable leaders is well documented. In a society increasingly obsessed with credentials, being genetically engineered is like having an Ivy-League M.B.A.: It is a marker of status that makes a candidate a safe bet for hiring, rather than an indicator of actual competence.

This is not to say that the genes associated with intelligence play no role in creating successful individuals — they absolutely do. They are an essential part of a positive feedback loop: When children demonstrate an aptitude at any activity, we reward them with more resources — equipment, private tutors, encouragement — to develop that aptitude; their genes enable them to translate those resources into improved performance, which we reward with even better resources, and the cycle continues until as adults they achieve exceptional career success. But low-income families living in neighborhoods with underfunded public schools often cannot sustain this feedback loop; the Gene Equality Project didn’t offer any resources besides better genes, and without these additional resources, the full potential of those genes was never realized.

We are indeed witnessing the creation of a caste system, not one based on biological differences in ability, but one that uses biology as a justification to solidify existing class distinctions. It is imperative that we put an end to this, but doing so will take more than free genetic enhancements supplied by a philanthropic foundation. It will require us to address structural inequalities in every aspect of our society, from housing to education to jobs. We won’t solve this by trying to improve people; we’ll only solve it by trying to improve the way we treat people.

This doesn’t necessarily mean that the Gene Equality Project is something that never needs to be repeated. Instead of thinking of it as a cure to an illness, we could think of it as a diagnostic test — something we would conduct at regular intervals to gauge how close we are to reaching our goal. When the beneficiaries of free genetic cognitive enhancements become as successful as the ones whose parents bought the enhancements for them, only then will we have reason to believe that we live in an equitable society.

Finally, let’s recall one of the arguments made during the original debate about legalizing genetic cognitive enhancements. Some proponents claimed that we had an ethical obligation to pursue cognitive enhancements because of the benefits to humanity that would accrue as a result. But there have surely been many geniuses whose world-changing contributions were lost because their potential was crushed by their impoverished surroundings.

Our goal should be to ensure that every individual has the opportunity to reach his or her full potential, no matter the circumstances of birth. That course of action would be just as beneficial to humanity as pursuing genetic cognitive enhancements, and it would do a much better job of fulfilling our ethical obligations.

This is one of the Reader Picks comments:

Mark
Philadelphia May 27

I have mixed feelings about the concept of this article. Surely, private schools confer numerous advantages to their students, who are from wealthy backgrounds and connections to higher education and corporate America.

But, look at Stuyvesant. The super intelligent and successful students are very often from middle class, lower-middle class, and even poor backgrounds. They are often first generation immigrants. They are just smart and hard working and their families care desperately about education.

Some kids are just smart, while others, are just average, or below average. You really think if you went into a school in the South Bronx and donated $1 billion the students would start cranking out perfect SATs?

Ask Zuckerberg how is $50 million donation to Newark public schools went. Darwinism is cruel, but some people aren't just cut out to be good students or white collar professionals.

Much of this has little to do with class and everything to do with drive and innate ability.

The Truth Shall Make You Free

Note Added in response to 2020 Twitter mob attack which attempts to misrepresent my views: This is not my research. I do not work on population structure or group differences in genomics. I also do not work on signals for recent natural selection. The post below discusses whether researchers should be forced to abandon important lines of investigation because of moral panics caused by misunderstanding of their results. What I told NYT reporter Amy Harmon at the time: These are serious, well-meaning researchers. You can't sensationalize their work and then force them to make loyalty pledges.

Racist inferences based on the results are the fault of the reader, not the authors of the papers or of this blog.

These NYTimes articles by Pulitzer Prize winner Amy Harmon, linking genetic science to racism and white supremacy, caused a sensation at ASHG 2018, a large annual meeting of genetics researchers.

Why White Supremacists Are Chugging Milk (and Why Geneticists Are Alarmed)

‘Could Somebody Please Debunk This?’: Writing About Science When Even the Scientists Are Nervous

Geneticists Criticize Use of Science by White Nationalists to Justify ‘Racial Purity’

In the second article above, Harmon writes

But another reason some scientists avoid engaging on this topic, I came to understand, was that they do not have definitive answers about whether there are average differences in biological traits across populations. And they have increasingly powerful tools to try to detect how natural selection may have acted differently on the genes that contribute to assorted traits in various populations.

What’s more, some believe substantial differences will be found. ...

The first talk I attended at ASHG this year is summarized below. The talk was oversubscribed, so I had to sit in the overflow room. One of the slides presented showed a table of specific complex traits, cross-referenced by different ancestry groups, indicating status of recent natural selection. The authors' results imply that different population groups have been experiencing differential selection over the last ~10k years: different selection pressures in different geographical locations. There were many talks at ASHG covering related topics, with similar conclusions. Advances in computational and statistical methods, together with large datasets, make it possible now to seriously investigate differential selection in recent human evolutionary history.

Given such results, how are researchers to respond when asked to categorically exclude the possibility of genetically mediated average differences between groups? 

We are scientists, seeking truth. We are not slaves to ideological conformity.

Building genealogies for tens of thousands of individuals genome-wide identifies evidence of directional selection driving many complex human traits.

S.R. Myers 1,2; L. Speidel 1
1) Department of Statistics, University of Oxford, Oxford, United Kingdom; 2) Wellcome Centre for Human Genetics, University of Oxford, Oxford, United Kingdom

For a variety of species, large-scale genetic variation datasets are now available. All observed genetic variation can be traced back to a genealogy, which records historical recombination and coalescence events and in principle captures all available information about evolutionary processes. However, the reconstruction of these genealogies has been impossible for modern-scale data, due to huge inherent computational challenges. As a consequence, existing methods usually scale to no more than tens of samples. We have developed a new, computationally efficient method for inferring genome-wide genealogies accounting for varying population sizes and recombination hotspots, robust to data errors, and applicable to thousands of samples genome-wide in many species. This method is >10,000 times faster than existing approaches, and more accurate than leading algorithms for a range of tasks including estimating mutational ages and inferring historical population sizes. Application to 2,478 present-day humans in the 1000 Genomes Project, and wild mice, provides dates for population size changes, merges, splits and introgressions, and identifies changes in underlying evolutionary mutation rates, from 1000 years, to more than 1 million years, ago. Using our mutational age estimates, we developed an approach quantifying evidence of natural selection at each SNP. We compared resulting p-values to existing GWAS study results, finding widespread enrichment (>2.5-fold in Europeans and East Asians) of GWAS hits among individual SNPs with low selection p-values (Z>6), stronger than the 1.5-fold increase observed at nonsynonymous mutations, and with enrichment increasing with statistical significance. We found evidence that directional selection, impacting many SNPs jointly, has shaped the evolution of >50 human traits over the past 1,000-50,000 years, sometimes in different directions among different groups. These include many blood-related traits including blood pressure, platelet volume, both red and white blood cell count and e.g. monocyte counts; educational attainment; age at menarche; and physical traits including skin colour, body mass index and (particularly in South Asian populations) height. Our approach enables simultaneous testing of recent selection, ancient natural selection, and changes in the strength of selection on a trait through time, and is applicable across a wide range of organisms.

Of course, all good people abhor racism. I believe that each person should be treated as an individual, independent of ancestry or ethnic background. (Hence I oppose Harvard's race-based discrimination against Asian Americans and favor Caltech's meritocratic approach to admissions.)

However, this ethical position is not predicated on the absence of average differences between groups. I believe that basic human rights and human dignity derive from our shared humanity, not from uniformity in ability or genetic makeup.

As a parent it is obvious to me that my children differ in innate aptitudes, preferences, and personalities. I love them equally: it would be wrong to condition this love on their specific genetic endowments.

Here is another set of ASHG talks I attended, on related issues:

Impact of Natural Selection on the Genetic Architecture of Complex Traits

Moderators: Shamil Sunyaev, Harvard Med Sch & Brigham & Women’s Hosp, Boston
Laura Hayward, Columbia Univ, New York

Evolution and maintenance of complex traits under natural selection has been a long-standing area of genetic research. Polygenic adaptation, stabilizing selection, and negative selection on new mutations can substantially impact the genetic architecture of diseases and complex traits, via direct selection on traits that are correlated with fitness and/or via pleiotropic selection. New methods are being developed to detect the action of natural selection at different time scales, including selection in contemporary humans. This session will discuss recent work on methods that analyze data from large cohorts to detect natural selection and evaluate its impact on diseases and complex traits. The application of these methods has substantially improved our understanding of polygenic disease and complex trait architectures, informing efforts to identify and interpret genetic variation affecting diseases and complex traits.

10:30 AM Polygenic architecture and adaptation of human complex traits. J. Pritchard. Howard Hughes Med Inst, Stanford.

11:00 AM Detection and quantification of the effect of selection and adaptation on complex traits. P. Visscher. Univ Queensland, Brisbane, Australia.

11:30 AM Observing natural selection in contemporary humans. M. Ilardo. Univ Utah & UC Berkeley.

12:00 PM Impact of negative selection on common variant disease architectures. A. Price. Harvard TH Chan Sch Publ Hlth, Boston.

More papers on recent natural selection and human complex traits:

https://infoproc.blogspot.com/2015/10/genetic-group-differences-in-height.html

https://infoproc.blogspot.com/2016/05/evidence-for-very-recent-natural.html

https://infoproc.blogspot.com/2017/06/complex-trait-adaptation-and-branching.html

https://infoproc.blogspot.com/2017/07/natural-selection-and-body-shape-in.html

Harvard Admissions on Trial

Now that the Harvard Asian American discrimination trial has started, let me share some previous correspondence with NYTimes reporters who are covering the proceedings.

... it's far too easy for the press to just report it as "Harvard's statistician disagrees with plaintiff's statistician" when in fact there are specific and important claims (e.g., regarding unhooked applicants) that are unanswered by Harvard.

Claim: when unhooked applicants are considered, Asians are discriminated against relative to all other groups.

Unhooked applicants are 95% of the total pool, but only ~2/3 of those admitted (see below). [ Unhooked = ordinary applicant = non-legacy, non-recruited athlete, etc. ]

http://infoproc.blogspot.com/2018/06/harvard-office-of-institutional.html

From the SFFA brief:

"The task here is to determine whether “similarly situated” applicants have been treated differently on the basis of race; “apples should be compared to apples.” SBT Holdings, LLC v. Town of Westminster, 547 F.3d 28, 34 (1st Cir. 2008). Because certain applicants are in a special category, it is important to analyze the effect of race without them included. Excluding them allows for the effect of race to be tested on the bulk of the applicant pool (more than 95% of applicants and more than two-thirds of admitted students) that do not fall into one of these categories, i.e., the similarly situated applicants. For special-category applicants, race either does not play a meaningful role in their chances of admission or the discrimination is offset by the “significant advantage” they receive. Either way, they are not apples.

Professor Card’s inclusion of these applicants reflects his position that “there is no penalty against Asian-American applicants unless Harvard imposes a penalty on every Asian-American applicant.” But he is not a lawyer and he is wrong. It is illegal to discriminate against any Asian-American applicant or subset of applicants on the basis of race. Professor Card cannot escape that reality by trying to dilute the dataset. The claim here is not that Harvard, for example, “penalizes recruited athletes who are Asian-American because of their race.” The claim “is that the effects of Harvard’s use of race occur outside these special categories.” Professor Arcidiacono thus correctly excluded special-category applicants to isolate and highlight Harvard’s discrimination against Asian Americans. Professor Card, by contrast, includes “special recruiting categories in his models” to “obscure the extent to which race is affecting admissions decisions for those not fortunate enough to belong to one of these groups.” At bottom, SFFA’s claim is that Harvard penalizes Asian-American applicants who are not legacies or recruited athletes. Professor Card has shown that he is unwilling and unable to contest that claim.

[ Card and Arcidiacono have exchanged criticisms of the other's analysis already, so Card's lack of response on this specific point is worthy of attention. ]

Will Harvard contest the claim that within the set of unhooked applicants, Asian Americans are discriminated against? As far as I know they have not.

The question about how unhooked applicants are treated has been discussed in college admissions circles for some time. See this from 2006:

https://infoproc.blogspot.com/2006/11/ugly-truth.html

Inside Higher Ed covers a panel called “Too Asian?” at the annual meeting of the National Association for College Admission Counseling. Particularly telling are the comments of a former Stanford admissions officer about an internal study which found evidence of higher admission rates for white applicants over Asians of similar academic and leadership qualifications (all applicants in the study were "unhooked" - meaning not in any favored categories such as legacies or athletes). 

[ So it is strange for Card / Harvard to claim that this specific question is not worth investigating! ]

Thanks to the lawsuit the results of a Harvard internal study in 2013 have been revealed, which concluded, like the Stanford study, that there was indeed discrimination against Asian American applicants. This will undoubtedly be discussed at trial.




The Content of their Character: Ed Blum and Jian Li.

Jian Li: "I have a message to every single Asian-American student in the country who is applying to college: your civil rights are being violated and you must speak up in defense of them. If you've suffered discrimination you have the option to file a complaint with the Office for Civil Rights. Let your voice be heard .. not only through formal means but also by simply letting it be known in your schools and your communities, in the press and on social media, that university discrimination is pervasive and that this does not sit well with you. Together we will fight to ensure that universities can no longer treat us as second-class citizens."

Update on NYTimes paywall

I posted before on miserly strategies to avoid buying a NYTimes subscription. It now appears to me their paywall is even wimpier than I had originally suspected. When I wrote the earlier post I hadn't yet experienced the paywall (either it wasn't on or I hadn't reached my limit of free articles for the month; I suspect the former). Having played around with it a bit, I've found the following.

If I try to read, for example, the Sidney Lumet obituary (btw, I highly recommend Dog Day Afternoon :-), the browser url bar shows the following when the subscription page has finally loaded:

http://www.nytimes.com/2011/04/10/movies/sidney-lumet-director-of-american-classics-dies-at-86.html?hp&gwh=A8B811D09B0F452C9A3F74E25512D060

If I eliminate all the cruft after "html" so that the url bar reads

http://www.nytimes.com/2011/04/10/movies/sidney-lumet-director-of-american-classics-dies-at-86.html

then reloading lets me read the article for free. This has worked for every article I've tried -- probably 20 or so by now.

Misers' methods for reading the NYTimes

Some people have pointed out to me that I am the cheapest (as in most miserly) person they know in my net worth category. I plead guilty.

The Times wants to charge me $35/month for unlimited digital access (that means on multiple devices, like mobile, tablet, computer). Now, I'm all for supporting journalism, and the Times in particular, but it seems kind of high to me. Let's see how it all works out for the Grey Lady. Perhaps a micropayment scheme would be better? (Has Google rolled their version out yet?)

Apparently they won't limit access to articles reached via link (i.e., from blogs, Twitter, search engine; see below for more details). This is strategic: they want their articles to be read, and to be influential, so don't want to frustrate potential readers who arrive via search or social network.

Therefore, I think you can just type the following into Google to get (free) access to daily NYTimes content (up to 5 articles per day; see note at bottom):

site:nytimes.com < today's date > < keywords >

i.e.,

site:nytimes.com march 29 2011 japan reactor

or

site:nytimes.com 2011/03/29 japan reactor

Soon someone will write a little web or mobile app to do exactly this kind of thing, mashing a nice graphical display with links that connect via Google or Twitter or whatever. Hmm ...

Here is a Twitter feed someone has already put up for this purpose. See also links in comments below.



*** It looks like search engine links are only good for 5 articles a day:

9. Can I still access NYTimes.com articles through Facebook, Twitter, search engines or my blog?

Yes. We encourage links from Facebook, Twitter, search engines, blogs and social media. When you visit NYTimes.com through a link from one of these channels, that article (or video, slide show, etc.) will count toward your monthly limit of 20 free articles, but you will still be able to view it even if you've already read your 20 free articles.

Like other external links, links from search engine results will count toward your monthly limit. If you have reached your monthly limit, you'll have a daily limit of 5 free articles through a given search engine. This limit applies to the majority of search engines.

New York Times nearing bankruptcy

They need some real business leadership, and they need it now. The Grey Lady is going down for the count thanks to the internet, craigslist and the recession. Will there be a bailout?

BusinessInsider: As expected, the New York Times's business operations began burning cash this quarter (until now, they had remained cash-flow positive). The company has recently made several wise moves that have postponed the date at which it will run out of cash. But the situation is still critical.

At the current rate of cash consumption, assuming no one-time expenses (highly unlikely), we estimate that the company will max out its current borrowing capacity in 4 quarters. At that point, it will owe about $1.2 billion in debt. This estimate does not include any payments on the company's $600+ million pension and benefit obligation, of which $181 million is due next year.

The bottom line: The New York Times Company remains on the brink of insolvency. There are also at least $1.5 billion of claims ahead of common shareholders of the company's assets should it file for bankruptcy. ...