Tag Archives: university

Less inspiring people in universities than in early school

A student claimed that fewer inspiring people are found in universities than in early school. Empirical checks of this would be interesting and would need a measure of inspiringness. A theoretical explanation is a tradeoff between multiple dimensions: subject matter competence, integrity, reliability, communication skills, being inspiring, etc. The tradeoff is on both the demand and the supply side. An inspiring competent person has many career options (CEO, politician, entrepreneur) besides academia, so fewer such people end up supplying their labour to the education sector.

On the demand side, a university has to prioritise dimensions on which to rank candidates and hire, given its salary budget and capacity constraints on how many job positions it has. Weighting competence more leaves less emphasis on inspiringness. Competing universities may prioritise different dimensions (be horizontally differentiated), in which case on average each institution gets candidates who have more of its preferred dimension and less of other dimensions.

As a side note, what an organisation says its priorities are may differ from its actual priorities, which are evidenced by behaviour, e.g., who it hires. It may say it values teaching with passion, but hire based on research success instead.

A constraint is a special case of a tradeoff. Suppose that given the minimum required competence, an employer wants to hire the most inspiring person. The higher this level of competence (teaching PhD courses vs kindergarten), the fewer people satisfy the constraint. At a high enough level of the constraint, there may be insufficient candidates in the world to fill all the vacant jobs. Some employers cannot fill the position, others will have just one candidate. Maximising inspiringness over an empty set, or a set of one, is unlikely to yield very inspiring people.

It may be inherently simpler to inspire with easier material, in which case even with equally inspiring people throughout all levels of education, the later stages will seem less inspiring.

Larger leaps through theory may be required as a subject gets more advanced, leaving less scope for inspiring anecdotes and real-life examples. The ivory tower is often accused of being out of touch with common experience. Parting with everyday life is partly inevitable for developing any specialised skill, otherwise the skill would be an everyday one, not specialised.

If inspiring people requires manipulating them, and more educated individuals resist manipulation better, then inspiring people gets more difficult with each level of education. Each stage of study selects on average the more intelligent graduates of the previous stage, so if smarter people are harder to manipulate, then those with higher levels of education are harder to inspire. On the other hand, if academics are naive and out of touch with the ways of the world, then they may be easier to manipulate and inspire than schoolchildren.

People accumulate interests and responsibilities in their first half of life. The more hobbies and duties, the less scope for adopting a goal proposed by some charismatic person, i.e., getting inspired by them. Later in life, many goals may have been achieved and people may have settled down for a comfortable existence. They are then less inclined to believe the need to follow a course that an inspiring person claims is a way of reaching their goals.

University incentives not to punish cheating

Universities have incentives not to expel cheaters, because these students would stop paying fees. By extension, there is a motive to avoid punishing academic dishonesty in any way that increases the chance of the student dropping out, like giving a cheater a failing grade. The university then gives a similar incentive not to punish academic dishonesty to its departments, who then pass on these incentives to faculty. In every university I have been in, it is far easier for a faculty member to do nothing about cheating – it requires no work, as opposed to a lot of bureaucracy documenting the cheating, imposing the punishment, dealing with the appeals, etc. There is no punishment for a faculty member who fails to report cheating, but to be fair, also no punishment for a false accusation of cheating, or an accusation that does not have sufficient evidence or gets overturned on appeal.

Even if a faculty member tries to punish academic dishonesty, the cheating student appeals to the university hierarchy and the higher-ups overturn the punishment. If not the first level of the hierarchy, then one of the higher levels. Thus even an inherently honest professor who for psychological reasons would be willing to spend the time to document academic dishonesty if it led to the cheater getting punished does not do so, because in the end there is no punishment.

A solution is to change university incentives: the students who are expelled because of cheating must pay their fees in full for their entire course of studies. A problem is that this leads to legal challenges because the student is not getting the education service but must pay for it. One solution is to require the tuition paid up front, non-refundable on expulsion for cheating. However, in this case students have to take a loan (which may be prevented by credit constraints or risk aversion) and may instead choose universities that do not charge them up front.

The university-side incentives also seem problematic if tuition is fully paid for expelled cheaters, because the university could save on the teaching costs by kicking out all the students on fabricated charges and keep the money. The long-term reputation cost for the university prevents such rip-offs.

A milder way to improve the university incentives is to require the cheater to re-take the course. This may delay the time at which the cheater can take follow-up courses that have the re-taken course as a prerequisite. The resulting delay in graduation may require the cheater to pay extra fees for the additional time, but the extra payment of course depends on the specific regulations of the university.

More efficient use of rooms and equipment during the shutdown

Instead of the labs, gyms and other rooms standing empty during the shutdown, the same isolation of people could be achieved by allocating each building or other resource to one person. Equipment from gyms or labs could be lent out for the duration of the shutdown, of course keeping a database of who borrowed what and making the borrower liable for its safe return. If only one person uses each object or building the whole time, then there is no cross-contamination or infection-spreading.

Excess demand could be rationed by lottery. Only the winner of the lottery for a resource would be allowed to use the resource, with large penalties for sharing. This would improve efficiency slightly, because one person instead of zero would be using each resource.

If the heat, water and electricity were turned off during the shutdown, then it might be more efficient to let the buildings stand empty, instead of having the utilities on and one person in each building or room. However, the lights in MIT buildings are still on at night, just like before the shutdown (and it seemed wasteful back then already).

The smartest professors need not admit the smartest students

The smartest professors are likely the best at targeting admission offers to students who are the most useful for them. Other things equal, the intelligence of a student is beneficial, but there may be tradeoffs. The overall usefulness may be maximised by prioritising obedience (manipulability) over intelligence or hard work. It is an empirical question what the real admissions criteria are. Data on pre-admissions personality test results (which the admissions committee may or may not have) would allow measuring whether the admission probability increases in obedience. Measuring such effects for non-top universities is complicated by the strategic incentive to admit students who are reasonably likely to accept, i.e. unlikely to get a much better offer elsewhere. So the middle- and bottom-ranked universities might not offer a place to the highest-scoring students for reasons independent of the obedience-intelligence tradeoff.

Similarly, a firm does not necessarily hire the brightest and individually most productive workers, but rather those who the firm expects to contribute the most to the firm’s bottom line. Working well with colleagues, following orders and procedures may in some cases be the most important characteristics. A genius who is a maverick may disrupt other workers in the organisation too much, reducing overall productivity.

Training programs should be hands-on and use the scientific method

The current education and training programs (first aid, fire warden, online systems) in universities just take the form of people sitting in a room passively watching a video or listening to a talk. A better way would be to interactively involve the trainees, because active learning makes people understand faster and remember longer. Hands-on exercises in first aid or firefighting are also more interesting and useful.

At a minimum, the knowledge of the trainees should be tested, in as realistic a way as possible (using hands-on practical exercises). The test should use the scientific method to avoid bias: the examiner should be unconnected to the training provider. The trainer should not know the specific questions of the exam in advance (to prevent “teaching to the test”), only the general required knowledge. Such independent examination permits assessing the quality of the training in addition to the knowledge of the trainees. Double-blind testing is easiest if the goal of the training (the knowledge hoped for) is well defined (procedures, checklists, facts, mathematical solutions).

One problem is how to motivate the trainees to make an effort in the test. For example, in university lectures and tutorials, students do not try to solve the exercises, despite this being a requirement. Instead, they wait for the answers to be posted. One way to incentivise effort is to create competition by publicly revealing the test results.

Directing help-seekers to resources is playing hot potato

In several mental health first aid guidelines, one of the steps is to direct the help-seeker to resources (suggest asking friends, family, professionals for help, reading materials on how to cope with the mental condition). This can provide an excuse to play hot potato: send the help-seeker to someone else instead of providing help. For example, the therapist or counsellor suggests seeing a doctor and obtaining a prescription, and the doctor recommends meeting a therapist instead.

The hot potato game is neither limited to sufferers of mental health issues, nor to doctors and counsellors. It is very common in universities: many people „raise awareness”, „coordinate” the work of others or „mentor” them, „manage change”, „are on the team or committee”, „create an action plan” (or strategy, policy or procedure), „start a conversation” about an issue or „call attention” to it, instead of actually doing useful work. One example is extolling the virtues of recycling, as opposed to physically moving recyclable items from the garbage bin to the recycling bin, and non-recyclable waste in the other direction. Another example is calling attention to mental health, instead of volunteering to visit the mentally ill at home and help them with tasks. Talking about supporting and mentoring early career academics, as opposed to donating part of one’s salary to create a new postdoc position, thereby putting one’s money where one’s mouth is.

All the seeming-work activities mentioned above allow avoiding actual work and padding one’s CV. Claiming to manage and coordinate other people additionally helps with empire-building – hiring more subordinates to whom one’s own work can be outsourced.

To motivate people to do useful work, as opposed to coordinating or managing, the desirable outcomes of the work should be clearly defined, measured, and incentivised. Mere discussions, committee meetings and action plans should attract no rewards, rather the reverse, because these waste other people’s time. More generally, using more inputs for the same output should be penalised, for example for academics, receiving more grant money should count negatively for promotions, given the same patent and publication output.

One way to measure the usefulness of someone’s activity is to use the revealed preference of colleagues (https://sanderheinsalu.com/ajaveeb/?p=1093). Some management and coordination is beneficial, but universities tend to overdo it, so it has negative value added.

Distinguishing discrimination in admissions from the opposite discrimination in grading

There are at least two potential explanations for why students from group A get a statistically significantly higher average grade in the same course than those from group B. The first is discrimination against A in admissions: if members of A face a stricter ability cutoff to be accepted at the institution, then conditional on being accepted, they have higher average ability. One form of a stricter ability cutoff is requiring a higher score from members of A, provided admissions test scores are positively correlated with ability.

The second explanation is discrimination in favour of group A in grading: students from A are given better grades for the same work. To distinguish this from admissions discrimination against A, one way is to compare the relative grades of groups A and B across courses. If the difference in average grades is due to ability, then it should be quite stable across courses, compared to a difference coming from grading standards, which varies with each grader’s bias for A.

Of course, there is no clear line how much the relative grades of group A vary across courses under grading discrimination, as opposed to admissions bias. Only statistical conclusions can be drawn about the relative importance of the two opposing mechanisms driving the grade difference. The distinction is more difficult to make when there is a „cartel” in grading discrimination, so that all graders try to boost group A by the same amount, i.e. to minimise the variance in the advantage given to A. Conscious avoidance of detection could be one reason to reduce the dispersion in the relative grade improvement of A.

Another complication when trying to distinguish the causes of the grade difference is that ability may affect performance differentially across courses. An extreme case is if the same trait improves outcomes in one course, but worsens them in another, for example lateral thinking is beneficial in a creative course, but may harm performance when the main requirement is to follow rules and procedures. To better distinguish the types of discrimination, the variation in the group difference in average grades should be compared across similar courses. The ability-based explanation results in more similar grade differences between more closely related courses. Again, if graders in similar courses vary less in their bias than graders in unrelated fields, then distinguishing the types of discrimination is more difficult.

Pre-selected health insurance plans for visitors

A half-year visit to a US university under a J1 visa requires US health insurance. In the University of Pennsylvania, the website of the International Students’ and Scholars’ Office says that they have pre-selected some health insurance plans. According to their cover description and comparison websites, these plans offer significantly less cover than similarly-priced plans not pre-selected by U Penn. My spreadsheet comparing the health insurance options is public. Possibly I have missed some aspects of insurance that justify the price difference. Another explanation is that the pre-selection was done by people who do not themselves use these insurance plans (because they are not visitors to the US) and have little incentive to make an effort to choose the best plan. A more negative and less likely interpretation is that the insurance company is providing incentives (such as kickbacks) for the selectors at U Penn to direct visitors to expensive low-cover plans that are profitable for the insurer.

Gender equity either on paper or by forcing people to change research fields

Suppose that a university employs roughly equal numbers of men and women overall, but the proportions of the genders differ across research fields, or across research and administration, and the university wants gender equality within each subfield. Using the narrowest definition of a research field, each field has either one or zero people, so in the smallest fields, gender equality is impossible. From now on, the focus is on fields or administrative units that have at least two people.
Gender equity can be achieved on paper by redrawing the administrative boundaries or redefining research fields. A simple algorithm (not the only possible algorithm) is to form pairs of one male and one female employee and call each such pair an administrative unit. Larger units can be formed by adding many male-female pairs together. If the numbers of men and women are not exactly equal, then some single-gender pairs will be left over, but most administrative units will have perfect gender equality.
The same idea can be used less radically by reassigning people who do interdisciplinary work and could plausibly belong to multiple research fields. Each person who is „between” fields gets assigned to the field that has a smaller fraction of that person’s gender. This increases gender equality in both the field that the person joins and the field that the person left. The field with a bigger surplus of that person’s gender loses one of that gender, and the field with a smaller surplus gains one.
Other than reassigning people or redrawing administrative boundaries, gender equity requires inducing people to change their research fields. To some of my colleagues, directing researchers to change their area is ideologically unacceptable. However, if equity is the goal and people’s field change is necessary to achieve it, then several methods can be used. The inducements can be softer or harder. A hard inducement is a hiring policy (and job ads) that restrict hiring to only one gender. The same can be done with promotion and retention. If this policy was explicitly stated to everyone, then it would become more effective, and also more acceptable to people than when they are surprised with it upon applying for promotion.
Soft inducements consist of hints that one gender is preferred, which are usually stated in political doublespeak like „we are committed to equity” or „we are an equal opportunity employer”. If many more candidates of one gender apply, then giving all candidates an equal opportunity of getting hired does not result in equal proportions of men and women employed. I am in favour of clear guidelines and transparency, for example of explicitly stating in job ads and promotion policies that the underrepresented gender is preferred, and which gender is currently underrepresented. Clearly telling people that switching fields is good for their career is likely to have a bigger effect than the currently used hints.
It may be easier to shift the research areas of people who are earlier in their careers. Encouraging more young people of a given gender to go to an area where their gender is underrepresented is one way of inducing them to change their field (relative to their preference).
Current equity policies are focussing almost exclusively on the inflow of employees. Gender balance can also be improved by managing the outflow, for example by offering early retirement schemes to one gender, or expanding these to a wider age range for one gender. If there are gender differences in the propensity of accepting certain inducements to leave, then the same inducements can be offered to both genders (seemingly gender-neutrally), with the desired result that one gender exits more.

Giving oneself tenure

Senior academics tell juniors that an assistant professor does not have to get tenure at his or her current university, but “in the profession”, i.e. at some university. To extend this reasoning, one does not have to get tenure at all, just guarantee one’s ability to pay one’s living costs with as low effort as possible. Government jobs are also secure – not quite tenure, but close.
Economically, tenure is guaranteed income for life (or until a mandatory retirement age) in exchange for teaching and administrative work. The income may vary somewhat, based on research and teaching success, but there is some lower bound on salary. Many nontenured academics are obsessed about getting tenure. The main reason is probably not the prestige of being called Professor, but the income security. People with families seem especially risk averse and motivated to secure their job.
Guaranteed income can be obtained by other means than tenure, e.g. by saving enough to live off the interest and dividends (becoming a rentier). Accumulating such savings is better than tenure, because there is no teaching and administration requirement. If one wishes, one can always teach for free. Similarly, research can be done in one’s free time. If expensive equipment is needed for the research, then one can pay a university or other institution for access to it. The payment may be in labour (becoming an unpaid research assistant). Becoming financially independent therefore means giving oneself more than tenure. Not many academics seem to have noticed this option, because they choose a wasteful consumerist lifestyle and do not plan their finances.
Given the scarcity of tenure-track jobs in many fields, choosing the highest-paying private-sector position (to accumulate savings), may be a quicker and more certain path to the economic equivalent of tenure than completing sequential postdocs. The option of an industry job seems risky to graduate students, because unlike in academia, one can get fired. However, the chance of layoffs should be compared to failing to get a second postdoc at an institution of the same or higher prestige. When one industry job ends, there are others. Like in academia, moving downward is easier than up.
To properly compare the prospects in academia and industry, one should look at the statistics, not listen to anecdotal tales of one’s acquaintances or the promises of recruiters. If one aspires to be a researcher, then one should base one’s life decisions on properly researched facts. It is surprising how many academics do not. The relevant statistics on the percentage of graduates or postdocs who get a tenure-track job or later tenure have been published for several fields (http://www.nature.com/ncb/journal/v12/n12/full/ncb1210-1123.html, http://www.education.uw.edu/cirge/wp-content/uploads/2012/11/so-you-want-to-become-a-professor.pdf, https://www.aeaweb.org/articles?id=10.1257/jep.28.3.205). The earnings in both higher education and various industries are published as part of national labour force statistics. Objective information on job security (frequency of firing) is harder to get, but administrative data from the Nordic countries has it.
Of course, earnings are not the whole story. If one has to live in an expensive city to get a high salary, then the disposable income may be lower than with a smaller salary in a cheaper location. Non-monetary aspects of the job matter, such as hazardous or hostile work environment, the hours and flexibility. Junior academics normally work much longer than the 40 hours per week standard in most jobs, but the highest-paid private-sector positions may require even more time and effort than academia. The hours may be more flexible in academia, other than the teaching times. The work is probably of the same low danger level. There is no reason to suppose the friendliness of the colleagues to differ.
Besides higher salary, a benefit of industry jobs is that they can be started earlier in life, before the 6 years in graduate school and a few more in postdoc positions. Starting early helps with savings accumulation, due to compound interest. Some people have become financially independent in their early thirties this way (see mrmoneymustache.com).
If one likes all aspects of an academic job (teaching, research and service), then it is reasonable to choose an academic career. If some aspects are not inherently rewarding, then one should consider the alternative scenario in which the hours spent on those aspects are spent on paid employment instead. The rewarding parts of the job are done in one’s free time. Does this alternative scenario yield a higher salary? The non-monetary parts of this scenario seem comparable to academia.
Tenure is becoming more difficult to get, as evidenced by the lengthening PhD duration, the increasing average number of postdocs people do before getting tenure, and by the lengthening tenure clocks (9 years at Carnegie Mellon vs the standard 6). Senior academics (who have guarateed jobs) benefit from increased competition among junior academics, because then the juniors will do more work for the seniors for less money. So the senior academics have an incentive to lure young people into academia (to work in their labs as students and postdocs), even if this is not in the young people’s interest. The seniors do not fear competition from juniors, due to the aforementioned guaranteed jobs.
Graduate student and postdoc unions are lobbying universities and governments to give them more money. This has at best a limited impact, because in the end the jobs and salaries are determined by supply and demand. If the unions want to make current students and postdocs better off, then they should discourage new students from entering academia. If they want everyone to be better off, then they should encourage research-based decision-making by everyone. I do not mean presenting isolated facts that support their political agenda (like the unions do now), but promoting the use of the full set of labour force statistics available, asking people to think about their life goals and what jobs will help achieve those goals, and developing predictive models along the lines of “if you do a PhD in this field in this university, then your probable job and income at age 30, 40, etc is…”.