College Admissions--the musical (casting call)

Here's the casting call, from Playbill. (College admissions is interesting, and so is the labor market for theatrical performances...)

College Admissions Scandal Musical Ranked Now Accepting Submissions
BY DAN MEYER  FEB 21, 2020
 The casting call seeks performers ages 18–early 20s.

"The new musical Ranked, which follows the 2019 college admissions scandal, is now accepting video submissions for an upcoming industry presentation to be filmed by HBO for a documentary.

"The casting call seeks Non-Equity/Non-SAG-AFTRA performers ages 18–early 20s (to play 14–18 years old). To submit, send a video singing 32 bars of a contemporary pop or rock song (i.e. Pasek & Paul, Tom Kitt, Sara Bareilles), headshot and résumé to RankedCasting@gmail.com before February 26 at noon ET.

"Stephanie Klapper Casting will screen the audition tapes prior to an in-person casting call on March 2. Performers must be available for the entire rehearsal and presentation time period, March 16–20. A March 20 industry presentation at The Daryl Roth Theatre will be filmed by HBO."

Reading for marketplace designers from Andreessen Horowitz

Scott Kominers forwards this interesting reading list (which includes a nice summary of market design by him and Tom Eisenmann):

Reading for Marketplace Entrepreneurs

It appears on the Andreessen Horowitz website https://a16z.com/marketplace-100/ , which is well worth a look for those interested in starting a marketplace company, or maintaining one.

School choice, centralized and decentralized, in Japan, a century ago, by Tanaka, Narita and Moriguchi

I heard Yusuke Narita present this remarkable paper comparing centralized and decentralized school matching at a recent seminar at Stanford.  It uses a  data set involving both outcomes and rules (rules are data!) of a school choice system for elite schools in Japan from the turn of the last century

Meritocracy and Its Discontent: Long-run Effects of Repeated School Admission Reforms
 TANAKA, Mari  NARITA, Yusuke  MORIGUCHI, Chiaki

Abstract: "We study the impacts of changing school admissions systems in higher education. To do so, we take advantage of the world’s first known implementation of nationally centralized admissions and its subsequent reversals in early twentieth-century Japan. This centralization was designed to make admissions more meritocratic, but we find that meritocracy came at the cost of threatening equal regional access to higher education and career advancement. Specifically, in the short run, the meritocratic centralization led students to make more inter-regional and risk-taking applications. As high ability students were located disproportionately in urban areas, however, increased regional mobility caused urban applicants to supplant rural applicants from higher education. Moreover, these impacts were persistent: four decades later, compared to the decentralized system, the centralized system continued to increase the number of urban-born elites (e.g., top income earners) relative to rural-born ones.

" Our empirical setting is the first known transition from decentralized to nationally centralized school admissions. At the end of the 19th century, to modernize its higher education system, the Japanese government set up elite national schools (high schools or colleges) that served as an exclusive entry point to the most prestigious tertiary education (Yoshino, 2001a,b; Takeuchi, 2011). These schools later produced many of the most influential members of the society, including several Prime Ministers, Nobel Laureates, and founders of global companies like Toyota. Acceptance into these schools was merit-based, using annual entrance examinations. Initially, the government let each school run its own exam and admissions based on exam scores, similar to many of today’s decentralized K-12 and college admissions. The schools typically held exams on the same day so that each applicant could apply for only one school. Similar restrictions on the number of applications exist today in the college admission systems of Italy, Japan, Nigeria, and the UK.

"At the turn of the 20th century, the government introduced a centralized system in order to improve the quality of incoming students. In the new system, applicants were allowed to rank multiple schools in the order of their preference and take a single unified exam.1 Given their preferences and exam scores, each applicant is assigned to a school (or none if unsuccessful) based on a computational algorithm. The algorithm was a mix of the so called Immediate Acceptance (Boston) algorithm and Deferred Acceptance algorithm with a meritocracy principle imposed upfront. To the best of our knowledge, this instance is the first recorded, nation-wide use of any matching algorithm. Furthermore, for reasons detailed below, the government later re-decentralized and re-centralized the system several times, producing multiple natural experiments for studying the consequences of the different systems."

Coffee is good for you, and how it became a worldwide market--Ashok Rai at Williams College

First the good news from coffee science, via the NY Times

Is Coffee Good for You?
Yes! But it depends on the kind of coffee and the quantity.

"In moderation, coffee seems to be good for most people — that’s 3 to 5 cups, or up to 400 milligrams of caffeine.

“The evidence is pretty consistent that coffee is associated with a lower risk of mortality,” said Erikka Loftfield, a research fellow at the National Cancer Institute who has studied the beverage."
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And for those of you interested in the coffee market, here's a lecture by Ashok Rai that I would go to if I were near Williams College today:

Ashok Rai to Lecture on the Globalization of Coffee

"Ashok Rai, associate professor of economics at Williams College, will present a lecture titled “From Muslim to Christian: How Coffee Went Global.” The second of six talks in the college’s Faculty Lecture Series this semester, the lecture will take place on Thursday, Feb. 20, from 4:15 p.m. to 5:30 p.m. in Wege Auditorium. A reception will follow in Schow Atrium. The event is free and open to the public.

"Rai’s current research examines the globalization of coffee, drawing on history, literature, ecology, and on fieldwork in Central America and East Africa. "

Visa allocation, by Pathak, Rees-Jones and Sönmez

Here's a look at current U.S. visa allocation policies from a market design perspective.

Immigration  Lottery  Design:  Engineered  and  Coincidental  Consequences  of  H-1B  Reforms

Parag A. Pathak, Alex Rees-Jones, Tayfun Sönmez

NBER Working Paper No. 26767
Issued in February 2020
NBER Program(s):Labor Studies Program

Abstract: In response to increasing demand for high-skilled labor, the U.S. Congress legislated in 2005 that the H-1B visa program create 20,000 additional slots for advanced degree applicants on top of 65,000 slots open to all. Since then, the U.S. Customs and Immigration Service (USCIS) has implemented this policy through visa allocation rules that comply with this legislation. Following a directive in the April 2017 Buy American and Hire American Executive Order by President Trump, USCIS tweaked its H-1B visa allocation rule in 2019, in an explicit effort to increase the share of higher-skill beneficiaries, bypassing the need for Congressional approval to increase the number of advanced degree slots. The USCIS estimated that the rule change, engineered solely for this objective, would increase the number of higher-skill beneficiaries by more than 5,000 at the expense of lower-skill beneficiaries. In this paper, we characterize all visa allocation rules that comply with the legislation. Despite specifying rigid caps, we show that the legislation still allows for rules that can change the number of high-skill awards by as many as 14,000 in an average year. Of all rules that comply with the legislation, the 2019 rule adopted by the Trump administration produces the best possible outcome for higher-skill applicants and the worst possible outcome for lower skill applicants. We also discover that each of the two previous and much less known changes to the H-1B visa allocation rule resulted in more substantial changes to the share of higher-skill beneficiaries than the 2019 reform. The distributional effects of these earlier reforms in 2006 and 2008, however, were motivated by logistical considerations, potentially without understanding of their importance for the rate of higher-skill awards.

Market design and algorithmic criminal justice--by Jung, Kannan, Lee, Pai, Roth and Vohra

When fairness isn't your only goal, your other goals may help you choose among competing definitions of fairness.

Fair Prediction with Endogenous Behavior
Christopher Jung, Sampath Kannan, Changhwa Lee, Mallesh M. Pai, Aaron Roth,and Rakesh Vohra
February 17, 2020

Abstract: There  is  increasing  regulatory  interest  in  whether  machine  learning  algorithms  deployed  in  consequential domains (e.g.  in criminal justice) treat different demographic groups “fairly.”  However, there are several proposed notions of fairness, typically mutually incompatible.  Using criminal justice as an example,  we study a model in which society chooses an incarceration rule.  Agents of different demographic groups differ in their outside options (e.g.  opportunity for legal employment) and decide whether to commit crimes.  We show that equalizing type I and type II errors across groups is consistent with the goal of minimizing the overall crime rate; other popular notions of fairness are not.
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And here's a blog post about the paper by one of the authors:

Fair Prediction with Endogenous Behavior
Can Game Theory Help Us Choose Among Fairness Constraints?

"...The crime-minimizing solution is the one that sets different thresholds on posterior probabilities (i.e. uniform thresholds on signals) so as to equalize false positive rates and false negative rates. In other words, to minimize crime, society should explicitly commit to not conditioning on group membership, even when group membership is statistically informative for the goal of predicting crime.

"Why? Its because although using demographic information is statistically informative for the goal of predicting crime when base rates differ, it is not something that is under the control of individuals --- they can control their own choices, but not what group they were born into. And making decisions about individuals using information that is not under their control has the effect of distorting their dis-incentive to commit crime --- it ends up providing less of a dis-incentive to individuals from the higher crime group (since they are more likely to be wrongly incarcerated even if they don't commit a crime). And because in our model people are rational actors, minimizing crime is all about managing incentives. "

Medical Licensing Exam (USMLE Step 1) to change from grades to pass/fail, to prevent over-reliance by residency programs

Among the concerns surrounding residency applications, interviews and matching is that the USMLE step 1 exam scores play an exaggerated role in determining who gets which residencies.  The Board of Medical Examiners is about to change that, with a new policy that will only report pass/fail rather than exam grades.

USMLE Program Announces Upcoming Policy Changes

"PHILADELPHIA, PA (February 12, 2020) – Today, the Federation of State Medical Boards (FSMB) and the National Board of Medical Examiners® (NBME®), co-sponsors of the United States Medical Licensing Examination® (USMLE®), announced upcoming policy changes to the USMLE program.

• Changing Step 1 score reporting from a three-digit numeric score to reporting only pass/fail;

• Reducing the allowable number of exam attempts on each Step or Step Component from six to four; and

• Requiring all examinees to successfully pass Step 1 as a prerequisite for taking Step 2 Clinical Skills. 

"These new policies will continue to enable the USMLE program to provide high-quality assessments for the primary user of exam results (state medical boards) while also addressing other considerations, such as exam security and unintended consequences of secondary score uses. The secondary uses of Step 1 scores for residency screening, in particular, have been the focus of extensive discussion over the past year at the FSMB and NBME, within the USMLE program, and with multiple stakeholders within the broader medical education and regulatory communities.

“These new policies strengthen the integrity of the USMLE and address concerns about Step 1 scores impacting student well-being and medical education,” said Humayun Chaudhry, DO, MACP, President and CEO of the FSMB. “Although the primary purpose of the exam is to assess the knowledge and skills essential to safe patient care, it is important that we improve the transition from undergraduate to graduate medical education.”

“The USMLE program governance carefully considered input from multiple sources in coming to these decisions. Recognizing the complexity of the environment and the desire for improvement, continuation of the status quo was not the best way forward,” reported Peter Katsufrakis, MD, MBA, President and CEO of NBME. “Both program governance and staff believe these changes represent improvements to the USMLE program and create the environment for improved student experiences in their education and their transition to residency." 

These policy changes are currently planned to be phased in over the next 11-24 months. For specific information on each policy, consult the link to the detailed statements accompanying each policy change. A podcast supplementing the information contained in this announcement is also available here."

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Here's some more detail:

Change to pass/fail score reporting for Step 1

"The USMLE program will change score reporting for Step 1 from a three-digit numeric score to reporting only a pass/fail outcome. A numeric score will continue to be reported for Step 2 Clinical Knowledge (CK) and Step 3. Step 2 Clinical Skills (CS) will continue to be reported as Pass/Fail. This policy will take effect no earlier than January 1, 2022 with further details to follow later this year.

...

"The FSMB and NBME believe that changing Step 1 score reporting to pass/fail can help reduce some of the current overemphasis on USMLE performance, while also retaining the ability of medical licensing authorities to use the exam for its primary purpose of medical licensure eligibility. The USMLE co-sponsors also believe that moving to pass/fail reporting of Step 1 while retaining a scored Step 2 CK represents a positive step toward system-wide change, while limiting large-scale disruption to the overall educational and licensing environment.

"The FSMB and NBME view this change as an important first step toward facilitating broader, system-wide changes to improve the transition from undergraduate to graduate medical education. The two organizations remain actively involved in the additional work sparked by InCUS, that of a broader system-wide review of the UME-GME transition that is being undertaken by the organizations in the Coalition for Physician Accountability **. As this future work develops, and as additional system-wide changes may unfold, including advances in reliable and holistic assessment of the training of physicians, the USMLE program will offer its resources and partnership."

Marketplace Design: summer school at Paris School of Economics in June

Olivier Tercieux forwarded this announcement:

THE DESIGN OF MARKET PLACES - Recent development in matching theory and empirical methods of matching  June 22 to June 26, 2020

"Allocation procedures have recently become a new and exciting field of economic research, with a wide range of applications. Since the seminal work by Gale and Shapley (1962) and Shapley and Shubik (1971), matching theory has developed and matured to a point where matching theorists could guide designs of medical match and other entry-level labor markets, school choice, course allocation and organ donation, among others. This course will introduce you to the frontier of research, including theoretical developments, applications, and empirical analysis"

The professors are:
•       Olivier Tercieux, Two-sided matching theory and application to school choice
•       Atila Abdulkadiroglu, Empirics of school choice
•       Alfred Galichon, Matching theory with transfers: optimal transport and economic applications

Computation in transplantation--conference in March

Here's an announcement:

"AiTraC 2020, the inaugural meeting on AI solutions for transplantation that will be held March 27-28, 2020 in South San Francisco, CA.

"CareDx, the Paris Transplant Group, and Cibiltech are cohosting AiTraC 2020. This meeting will bring together healthcare professionals and AI technology experts to discuss how data solutions can improve transplant patient outcomes. Confirmed speakers include Nobel Laureate Alvin Roth, Duke Chair of Surgery Allan Kirk, and ex-CTO of WebMD and double lung transplant recipient David Guthrie.
...
“I often say that AI will not replace clinicians, but the clinicians who use AI solutions will replace the clinicians who do not. This is a first meeting to discuss how we can best use AI to support the care for patients. And by AI, I mean augmented as well as artificial intelligence,” said Alexandre Loupy, MD, Professor at the Paris Transplant Group. “Tools using machine learning for transplant care are now a reality, and the community will come together to discuss how to best implement these solutions and shape the future of care.”


And here's the conference site, with details still to come:
AiTraC: The Inaugural AI in Transplantation Meeting
2020
MARCH 27 - 28
1 Tower Place
South San Francisco, CA