The Productive Postdoc: Do Working Conditions Affect Outcomes? Geoff Davis Visiting Scholar and Survey Principal Investigator Sigma Xi, The Scientific Research Society

Improving the Postdoctoral Experience Many calls for changes to the postdoc –National Academies, AAU, NPA, etc Big question: What, if anything, works?

What Works?  Changes have costs (money, time)  Do benefits justify investments?  What should priorities be?  What gives the biggest bang for the buck?  These are empirical questions

Our “Experiment”  Postdoc administration takes place largely at the level of the PI  Tremendous variability in conditions from lab to lab  Recent, limited introduction of new practices  Natural experiment  Ask postdocs about their working conditions  Ask about how well they are doing  Find conditions associated with positive outcomes

Sigma Xi Postdoc Survey  Ran a big web survey  Contacted 22,400 postdocs at 47 institutions  ~40% of all postdocs in US  Overall response rate: 38%*  (*See tech report for details)

Our Sponsor The Alfred P. Sloan Foundation Alfred P. SloanMichael Teitelbaum

Additional Support Werthheim Fellowship, Harvard University

Partner Organizations  National Postdoc Association  Science’s Next Wave  NBER/Sloan Scientific Workforce Group

Sketch of Our Analysis Create measures of inputs (working conditions, demographics, etc) and outcomes Build linear models to test hypothesis that inputs have an impact, gauge magnitude of impact (if any)

How Do We Determine Success? Ideal: track people down in 10 years, see what they are doing / have done Problems: –Very expensive –Takes 10 years to learn anything Driving via the rear view mirror Instead, look at immediate proxies for longitudinal data

Outcomes What makes for a “good” experience? No single “best” measure –Different people want different things Create collection of outcome measures –Look at impact of inputs on each

Subjective Outcome Measures Subjective success measure –Overall satisfaction, preparation for independent research, quality of training in research / teaching / management Advisor relations measure –How is your advisor doing? Is s/he a mentor? How would s/he say you are doing? Generate numerical scores by summing Likert scored answers

Objective Outcome Measures Absence of Conflict/Misconduct –Has postdoc had a conflict with advisor? Has s/he seen misconduct in the lab? Productivity –Rate at which papers submitted to peer reviewed journals

Outcome Measure Distributions

Outcome Measure Details Correlations all fairly low –Subjective success and advisor relations ~0.45 –Other pairwise correlations all < 0.2

Our Explanatory Variables Model outcomes as function of explanatory variables –Field of research –Institution –Basic demographic variables Sex Citizenship Minority/Majority Status Type of degree (MD vs PhD) –Total time as a postdoc –“Working Conditions”

“Working Conditions” How do we measure working conditions? Inspiration comes from various calls for changes –Look at rate of implementation

Recommended Changes 5 broad classes of recommended changes –Pay people more –Fellowships rather than assistantships –Better benefits –More structured oversight –Transferable skills training

Measures of Working Conditions Salary measure –log(annual salary), full-time people only Independent Funding measure –Dummy variable, 1 if fellowship, 0 otherwise Benefits measure –Count of different benefits received (health insurance, retirement plan, etc)

Structured Oversight Structured Oversight measure –Count of administrative measures in place Individual development plans Formal reviews Policies (authorship / misconduct / IP / etc) Letters of appointment –High values = lots of structure, low = little

Training Transferable Skills Training measure –Count of areas in which postdoc reports receiving training –Grant writing, project/lab management, exposure to non-academic careers, negotiation, conflict resolution, English language, etc –High values = training in lots of areas –Low values = no training in lots of areas

Working Conditions Distributions

Working Conditions Details Again, correlations all fairly low –Structured oversight and skills training ~0.30 –Other pairwise correlations all < 0.15

What Has Biggest Impact? Who is most satisfied, most productive, etc? People with –Independent funding? –High salaries? –Lots of benefits? –Lots of structured oversight? –Lots of types of transferable training?

Simple Analysis Crude analysis: compare satisfaction, productivity, etc for people in appointments with –Fellowships / other funding –High / low salaries –High / low benefits –High / low structure –High / low training

Independent Funding FellowshipOther % satisfied74%70% Advisor grade (0=F, 4=A) % reporting conflicts 14% Papers submitted / year

Salary Highest 25%Lowest 25% % satisfied71%68% Advisor grade (0=F, 4=A) % reporting conflicts 16%13% Papers submitted / year 1.2

Benefits Highest 25%Lowest 25% % satisfied76%62% Advisor grade (0=F, 4=A) % reporting conflicts 11%18% Papers submitted / year

Structured Oversight High structureLow structure % satisfied80%60% Advisor grade (0=F, 4=A) % reporting conflicts 9%21% Papers submitted / year

Transferable Skills Training High trainingLow training % satisfied83%56% Advisor grade (0=F, 4=A) % reporting conflicts 10%17% Papers submitted / year

Regression Coefficients

Take Home Message #1 Structured oversight and transferable skills training make a big difference

Causality? We have correlation. Is there causation? –Psych literature gives reasons to believe in causation Alternative explanations 1.Structure and training attract people who are intrinsically more satisfied / productive / successful 2.Structure / training correlate with some other unobserved factor –Advisors are effective managers / have more resources –Postdocs take more initiative / are better organized / etc

Causality? 2 classes of explanation 1.Structure/training attract intrinsically more productive people 2.Structure/training directly cause productivity or are indicators for some causal mechanism (Some combination of 1 & 2 also possible) Should be able to differentiate between 1 & 2 by looking at people with multiple appointments

Intrinsic vs. Time-Localized

Causality? Add in terms that allow for change in slope of papers(t) curve starting at beginning of most recent postdoc Equivalent to adding interactions with ratio (months in current postdoc / total months as postdoc) to regression model Training appears to have a time-localized effect Other inputs ambiguous

Don’t Pay Postdocs? Not saying postdocs shouldn’t be paid! –Hard to attract US students to science if you don’t pay them Maslow’s hierarchy of needs –Must meet basic physical security needs first –Living wage, basic benefits More nuanced interpretation of data: beyond a certain threshold, structure and training matter more than compensation Institutional “postdoc tax” to support service provision?

More Details Look at individual components of structure and training measure What specific measures have the greatest impact?

Impact One measure appears to have significant impact all 4 outcomes: –Research / career plans Written plans Plans that spell out what both postdoc and PI will do Advocated by FASEB, National Academies

Plans Compare those with such a plan to those without: –Much less likely (~40%) to be dissatisfied –Much less likely (~30%) to have conflicts After controlling for field, institution, demographics: –Submitted ~14% more papers for publication

Why? Plans: –Expectation setting device Postdocs without plans were much more likely to report PI had not lived up to expectations –Contract Research shows that people are more likely to live up to explicit (esp. written) commitments –Forces postdocs to take responsibility for their careers early More time to take advantage of training opportunities –Time management device Mechanism for focusing effort

Take Home Message #2 Individual development plans make a big difference

Additional Measures  Several other measures show concrete benefits:  Teaching experience  Exposure to non-academic careers  Training in proposal writing  Training in project management  Training in ethics

Policy Implications  For postdocs, more effective to invest additional dollars in management than in salaries  Management at all levels:  Infrastructure for institutional oversight / training  Management training for PIs  Management training for postdocs

Further information  More information at  Workshop (with NPA) in January 2006  Contacts  Geoff Davis, PI,  Jenny Zilaro, Project Manager,

Extra Material

End Products  Sigma Xi:  Highlights in May/June issue of American Scientist  Tech reports (2 out now, more to come)  Scholarly paper this fall  NPA: Analyses of various topics  NBER SEWP  Workshop in January 2006

Aside: Postdoc Definition Half a dozen different definitions –AAMC, AAU, FASEB, NAS, NSF BUT if you read and compare them, they all say the same thing –Only substantive difference is that FASEB includes narrow subset of clinical fellows –(We excluded them from this analysis) Most people don’t fully satisfy definition anyway

Postdoc Definition The appointee has a PhD or equivalent degree, the degree was received recently, the appointment is temporary, the purpose of the appointment is training for a research career, the appointment involves substantially full-time research or scholarship, the appointee is expected to publish the results of his or her research, and the appointee works under the supervision of a senior scholar or a department in a university or research institution.

Survey Non-Response  30-second summary of non-response analysis:  Non-citizens and African Americans appear to be slightly under-represented  No evidence of bias based on level of satisfaction (respondents not overly disgruntled)

Survey Non-Response Survey respondents atypical in one important way –Participating institutions all had PDO, PDA, or administrator interested in postdoc affairs Participating institutions probably better off than average

Salaries Median salary: $38,000 Up from $28,000 in 1995

Inflation A 10% increase above inflation since 1995 –($28,000 in 1995 = $34,700 in 2004) NIH budget doubled over the same period (in inflation-adjusted dollars)

Experience Salaries increase at about 2.9% per year of experience

Field Overall average = $39,300 Average salary in most common fields ranges from $37,500 to $40,000 Higher: –Electrical engineering ($45,000) –Physics ($42,600) –Oncology ($41,400) –Materials science ($41,200) Lower: –Ecology ($35,600)

Institution Type Govt labs pay 20% more than average Public universities pay 9% less than average

Taxes Tax loophole: some postdocs don’t have to pay FICA (7.65% of income) –23% benefit –New IRS rules affect this Tax penalty: some postdocs pay extra self-employment tax (also 7.65% of income) –12% pay –Independent contractor status carries hidden tax penalty! Potential $6,000 impact on salary

Part-time 3% report part-time status Average hours worked previous week: 45

Hours 51 hours/week median Postdoc hourly wage ~ $14.90

Hours 51 hours/week median Postdoc hourly wages = $14.90/hour Harvard janitors = $14.00/hour

Foreign Postdocs International Men and Women of Mystery

Basic Demographics  Citizenship:  Citizens:40%  Permanent residents:6%  Temporary visa holders:54%  PhD:  US PhD:53%  Non-US:47%

Non-US PhDs  Where PhD earned:  Almost 80% of postdocs on temporary visas earned their PhDs outside the US  Non-US PhDs invisible in NSF stats AllUS citizens (41%) Permanent residents (6%) Temporary (53%) US53%97%51%21% Elsewhere47%3%49%79%

Non-US PhDs  Where non-US PhDs were earned:  Country of citizenship86%  Different country, same continent7%  Different continent7%

Temporary Visa Holders Citizenship China24% India11% Germany6% South Korea6% Japan6% Canada5% France5% United Kingdom4% Spain3% Italy3% Top 1073% Source of PhD China18% India10% Japan8% UK8% Germany8% France6% Canada5% South Korea4% Israel3% Spain3% Top 1073%

Non-US Postdocs and PhDs  China and India dominate  Market share of postdocs comparable to share of doctorates (China = 23%, India = 10%)  Next largest LDC is Argentina, #16 for both citizenship and PhDs, with 1% of each

Temporary Visa Holders by Field Electrical engineering72% Physics67% Chemistry61% Molecular biology58% Biochemistry57% Cell biology57% Earth sciences52% Ecology36% Psychology21%

Broad Field Temporary visasNon-US PhDs Life/health sciences 52%47% Physical sciences / engineering 63%44% Social sciences23%18%

Other Characteristics US postdocs:  49% men/51% women  69% married  33% have children  Median age: 33 International postdocs:  65% men/35% women  69% married  35% have children  Median age: 33

Other Characteristics  One notable difference for married postdocs  US postdocs: 15% have non-working spouse  Non-citizen postdocs: 44% have non-working spouse  Some visas (e.g. H) don’t have provision for spouse to work

Domestic vs International: Papers  International postdocs publish more  Average peer-reviewed publications as a postdoc  Citizens/PR2.6  Temporary3.3 (27% more)  Difference is smaller (.1 papers/year) after we control for time as a postdoc, field, institution, sex, but statistically significant

Domestic vs International: Hours  Non-citizens work longer hours  Average weekly hours worked  Citizens/PR50  Temporary52 (4% more)  Difference is smaller (1.3 hours/week) after we control for time as a postdoc, field, institution, sex, but still statistically significant

Domestic vs International: Salary  BUT non-citizens are paid substantially less  Median annual salary  Domestic$40,000  International$37,000 (8% less)  Domestic postdocs earn $2,200/year more than international postdocs after controlling for field, institution, sex, time as a postdoc, and funding mechanism

Domestic vs International: Grants  Citizens write more grant proposals (results suggest mostly fellowship applications)  Grant proposals written while a postdoc  Citizens1.6  Non-citizens1.1 (31% fewer)  International postdocs write fewer grant proposals even after controlling for field, institution, sex

Domestic vs International: Satisfaction  Non-citizens report slightly lower levels of satisfaction with the postdoc experience  Average satisfaction (-2 = dissatisfied / 2 = satisfied)  Citizens/PR0.8  Temporary0.6  Difference disappears when one controls for salary, discipline, institution, sex, and time as a postdoc

Security Problems  To what extent have US national security regulations affected your ability to do the following: (% responding “Some” or “A lot”)  Conduct your research in the US:30%  Travel outside the US to conduct your research:40%  Visit your country of citizenship:55%  Re-enter the US after leaving the country:57%  Bring your immediate family members to the US:36%  Free-text comments express considerable frustration

More information  More information at  Contacts  Geoff Davis, PI,  Jenny Zilaro, Project Manager,

Survey Responders  Difficult to obtain ground truth for assessing results  Plan: compare results of pilot survey to known values for one institution with good records  Reality: survey revealed that the institution in question was missing lots of postdocs (~10% of the local population)

Survey Responders  Fortunately we found an alternative with better records  Differences in response rates consistent with levels of variation in a random sample for  Sex  Citizenship  Minority status  No strong evidence of non-response bias

Further Non-response Analysis  Survey literature: propensity to respond is a continuous variable  Early responders: high propensity  Late responders: lower  Non-responders: lowest  Idea is that non-responders are more similar to late responders than early responders  Compare early and late responders. Differences suggest potential non-response bias.

Non-response Bias?  Who are missing 66% of postdocs?  No significant difference between early and late responders by  Sex  Overall satisfaction  Significant but small difference by citizenship (p ~0.04)  Early responders:~49% citizens  Late responders: ~45% citizens  Non-citizen postdocs are probably slightly underrepresented

Domestic vs International: Satisfaction  Non-citizens report slightly lower levels of satisfaction with the postdoc experience  Average satisfaction (-2 = dissatisfied / 2 = satisfied)  Citizens/PR0.8  Temporary0.6  Difference disappears when one controls for salary, discipline, institution, sex, and time as a postdoc

Settlement Interests  Level of interest (0=None, 2=High) in settling in various regions (ignoring visa issues)* USEuropeAsia US citizens European citizens Asian citizens

Settlement Interests  Level of interest (0=None, 2=High) in settling in various regions (ignoring visa issues)* USEuropeAsia US citizen, US PhD US citizen, non-US PhD European citizen, US PhD European citizen, non-US PhD Asian citizen, US PhD Asian citizen, non-US PhD