Postdoc studying combustion modeling, science contributor for Ars Technica, husband. Not necessarily in that order.
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Jet engines are a major part of aviation today, and this great...

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Jet engines are a major part of aviation today, and this great video from the new LIB LAB project breaks down how jet engines operate. It focuses especially on the subject of combustion, in which fuel-air mixtures are burned to generate power and thrust. By breaking fuels down into simpler compounds, jet engines are able to accelerate exhaust gases, which creates thrust. They even provide instructions for an effervescence-driven bubble rocket so that kids can (safely!) experiment with propulsion at home. (Video credit: LIB LAB/Corvallis-Benton County Public Library)

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281 days ago
Check this out—science communication video on jet engines made by my PhD student!
Corvallis, OR
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Open letter to my family in Ohio: I am still coming home for Thanksgiving this year

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Dear Mom and Pop,

This was going to be an awkward year for us from the start. Thanksgiving is normally a time when we, two dozen immigrant Jews and first-generation Americans, come together to eat a turkey stuffed with oranges, served with a side of smoked fish and a dozen competing salads.

Before the election, I thought the greatest thing that would divide our dinner table would be my recently adopted vegetarianism. But us Jews are all about dietary restrictions. Eight breadless days of weight loss every year during Passover. Fasting from food and water every year for the day of atonement. Two sets of plates for Shabbat and for everyday. I was certain that refusing meat wouldn’t stop me from feeling embraced and loved at the table.

A russian salad feast courtesy of my friend Andrey Petrov

But then last week you voted for Trump. Jewish refugees from the Ukraine now living in Ohio voted for Trump. You have told me several times that Obama is the worst president in our lifetime. And so you voted for Trump.

This letter would not have been written if this were just about politics. Both of you have always voted conservatively. And I wouldn’t be this livid if it were just about privatization of health care, or import tariffs, or the unchecked negative externalities of infrastructure spending on energy extraction. The political tide goes in and out. How we run the country makes for a spirited debate over the Thanksgiving dinner table and I welcome our family’s contrary viewpoints. But this is not about politics.

Voting for Trump is clearly a vote for hate. I know you voted against Hillary, and not “in favor” of Trump, but the action is the same. Your vote signals to me that you see our fellow citizens as less than human. History shows where this leads and history is not just words in a textbook for us. You are choosing to ignore our past.

Donald Trump Says He’d ‘Absolutely’ Require Muslims to Register

We would have seven times as many cousins if it weren’t for the Nazis. You helped elect a fascist and are now complicit in what’s going to happen to families both in and outside of our country.

It is not unreasonable for people to think that fascists, if given power and an attempt to govern, will moderate their views. But history repeats itself.

“Several reliable, well-informed sources confirmed the idea that Hitler’s anti-Semitism was not so genuine or violent as it sounded, and that he was merely using anti-Semitic propaganda as a bait to catch masses of followers and keep them aroused, enthusiastic, and in line for the time when his organization is perfected and sufficiently powerful to be employed effectively for political purposes.”
“You can’t expect the masses to understand or appreciate your finer real aims. You must feed the masses with cruder morsels and ideas like anti-Semitism. It would be politically all wrong to tell them the truth about where you really are leading them.”

I take Trump at his hate-filled words. Last time we spoke, you did not. You said he probably wouldn’t be fulfilling any of his promises, like the ones to register Muslims or deport Latinos. However, even if you do believe that his campaign was only hype, you still ignored despicable behavior and rhetoric. Normalizing racism is itself an act of racism.

Some positions are binary. You either care about the protection of minorities or you do not. I have friends now who will stand in the same shoes that my grandparents stood in before. And you knew, regardless of your enthusiasm for Trump’s economic policies, that these people would suffer. The increasing number of graffitied swastikas, along with other vile behaviors now edging into the mainstream, are the kind of atrocities your vote was supposed to suppress.

You taught me that my highest responsibility as a Jew is to never forget, to fight against discrimination. This was a common refrain told to me during seven years of Hebrew school. I take that responsibility seriously and that is what I am trying to do now. Elie Wiesel said “We must take sides. Neutrality helps the oppressor, never the victim. Silence encourages the tormentor, never the tormented.”

I understand why you voted to put Trump in office. It’s just hard for me to forgive you for it. And now is not the time to give bigotry a pass. I’m trying to live by the values you taught me, which is why I am only asking you to take our President at his word. And when he tells you of his bigoted promises to force members of a religion to register, you should be outraged.

I am coming home this Thanksgiving and it’s going to be painful, most of all for me. I try to be empathetic with how you feel about the state of our country, but what I do not understand is how you think that voting for a racist and hate-filled demogogue with no political experience is going to promote growth and peace. At best, it will alienate over half of this country, and at worst, history will repeat itself.

I am coming home because I want to believe the love that brings us together at Thanksgiving is strong enough to not only include a vegetarian, but also strong enough to allow you to understand my perspective and possibly even change your minds. I need my family with me in this fight.

Your son,

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386 days ago
I just wrote this letter to my family. Thanks to those of you who helped convince me to do the hard thing and go back and tell them in person how I feel.
The Haight in San Francisco
386 days ago
Good luck with the trip home. I have no idea how I'm going to deal with this when the time comes. (I'm living overseas and won't be moving back until right at the holidays, so I get a pass this year). (And this was beautifully written.)
385 days ago
Good luck, Samuel, and good on you for believing there's even a possibility of understanding. It makes me think of the profound book I Am Asher Lev, which I read recently, and how communities work with their differences. It takes great courage. Thank you for sharing this.
385 days ago
This will be me in a few days too (with a family of trump supporters) although I won't be around Jews (I will be the only Jew though) but still celebrating pilgrims who were escaping for their religious freedom. I am sure they may just discount me for my background and we will avoid the subject but who knows. I am bringing some strong beer.. let us know how yours go as I would like to compare notes. Oh and I have just been through Brexit so to a degree I am dealing with deja vu of sitting with a family with a huge elephant in the room.
383 days ago
My love to you and yours, Sam.
375 days ago
Samuel, I want to thank you from the bottom of my heart for writing that letter to your family, and most of all, maybe, for sharing it with all of us. It's a beautifully written letter. I am so proud of you for being who you are, for starting and continuing to show up and nurture the incredible NewsBlur. You are such a good person, Samuel, you have a depth to you that eludes understanding. I wish you love, and peace too, and tenacity to persevere in these terrible days. Thank you so very much.
385 days ago
385 days ago
Corvallis, OR
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385 days ago
It hurts that this had to be written
Washington, DC

Pistons coach goes on tirade about 'racist and misogynistic' Donald Trump

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Detroit Pistons coach Stan Van Gundy has never been one to mince his opinions, so it was only a matter of time before he went on a rant after Donald Trump was elected president of the United States. 

Speaking to reporters prior to the Pistons’ NBA matchup against the Phoenix Suns on Wednesday, Van Gundy went on a nearly six-minute, unprompted tirade on the unconventional president-elect, who beat Hillary Clinton to the White House, saying he was ashamed of the public for voting in the 70-year-old.

Here is the full transcript of Van Gundy’s comments to the media:

“I didn’t vote for [George W.] Bush, but he was a good, honourable man with whom I had political differences, so I didn’t vote for him. But for our country to be where we are now, who took a guy who - I don’t care what anyone says, I’m sure they have other reasons and maybe good reasons for voting for Donald Trump - but I don’t think anybody can deny this guy is openly and brazenly racist and misogynistic and ethnic-centric, and say, 'That’s OK with us, we’re going to vote for him anyway’.

“We have just thrown a good part of our population under the bus, and I have problems with thinking that this is where we are as a country. It’s tough on [the team], we noticed it coming in. Everybody was a little quiet, and I thought, ‘Well, maybe the game the other night’. And so we talked about that, but then Aron Baynes said, ‘I don’t think that’s why everybody’s quiet. It’s last night’.

“It’s just, we have said - and my daughters, the three of them - our society has said, ‘No, we think you should be second-class citizens. We want you to be second-class citizens. And we embrace a guy who is openly misogynistic as our leader’. I don’t know how we get past that.

“Martin Luther King said, 'The arc of the moral universe is long, but bends toward justice’. I would have believed in that for a long time, but not today. What we have done to minorities… in this election is despicable. I’m having a hard time dealing with it. This isn’t your normal candidate. I don’t even know if I have political differences with him. I don’t even know what are his politics. I don’t know, other than to build a wall and ‘I hate people of colour, and women are to be treated as sex objects and as servants to men’. I don’t know how you get past that. I don’t know how you walk into the booth and vote for that.

“I understand problems with the economy. I understand all the problems with Hillary Clinton, I do. But certain things in our country should disqualify you. And the fact that millions and millions of Americans don’t think that racism and sexism disqualifies you to be our leader, in our country. We presume to tell other countries about human-rights abuses and everything else. We better never do that again, when our leaders talk to China or anybody else about human-rights abuses.

“We just elected an openly, brazen misogynist leader and we should keep our mouths shut and realize that we need to be learning maybe from the rest of the world, because we don’t got anything to teach anybody.

“It’s embarrassing. I have been ashamed of a lot of things that have happened in this country, but I can’t say I’ve ever been ashamed of our country until today. Until today. We all have to find our way to move forward, but that was - and I’m not even trying to make a political statement. To me, that’s beyond politics.

“You don’t get to come out and talk about people like that, and then lead our country and have millions of Americans embrace you. I’m having a hard time being with people. I’m going to walk into this arena tonight and realize that - especially in this state - most of these people voted for the guy. Like, [expletive], I don’t have any respect for that. I don’t.

“And then you read how he was embraced by conservative Christians. Evangelical Christians. I’m not a religious guy, but what the hell Bible are they reading? I’m dead serious. What Bible are you reading? And you’re supposed to be - it’s different. There are a lot of different groups we can be upset at. But you’re Christians. You’re supposed to be - at least you pride yourself on being the moral compass of our society. And you said, ‘Yeah, the guy can talk about women like that. I’m fine with that’. He can disparage every ethnic group, and I’m fine with that.

“Look, I don’t get it. And I’m having a hard time taking it. I’m just glad that the people I’m with here - and I’ll include you guys, too - that I like. Because I’m going to have a hard time. I will say, one point of pride, I live in Oakland County, Michigan, and I was surprised, but Oakland County voted for Clinton. At least I can look around say, ‘We weren’t the ones putting that guy in office’.

“It’s incredible. I don’t know how you go about it, if you’re a person of colour today or a Latino. Because white society just said to you, again - not like we haven’t forever - but again, and emphatically, that I don’t think you deserve equality. We don’t think you deserve respect. And the same with women. That’s what we say today, as a country. We should be ashamed for what we stand for as the United States today.

“That’s it for me. I don’t have anything to say about the game tonight.”

All white people should model ourselves after Stan Van Gundy.

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394 days ago
Well said.
Corvallis, OR
393 days ago
New York
394 days ago
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391 days ago
puts his finger on the pain real well
Idle, Bradford, United Kingdom
395 days ago
395 days ago
I might actually have to start watching basketball
Brooklyn, NY

Barbagroup reproducibility syllabus

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Lockheed P-80A airplane (1946). Credit: NASA Commons. —A reminder to test your code.

After my short piece, “A hard road to reproducibility,” appeared in Science, I received several emails and Twitter mentions asking for more specific tips—both about tools and documents we use in the group to train the team about reproducibility.

In answer to popular demand, then, I have collected here what we could call the “Barba-group Reproducibility Syllabus.”

Top-10 Readings in Reproducibility

Early this year, my student Olivier and I were getting started writing a book chapter and later a full-length journal article; the first was about our reproducible-research workflow and the second on our CFD replication study. These represented about three years of work, not exclusively on this project, but taking most of the graduate student’s time. As part of our “pre-writing” tasks, we decided to build—collectively as a group—our list of Top 10 papers discussing reproducible research in computational science. Here’s our current reading list (modified from our first version of Feb. 2016):

  1. Schwab, M., Karrenbach, N., Claerbout, J. (2000) Making scientific computations reproducible, Comp. Sci. Eng. 2(6):61–67, doi: 10.1109/5992.881708
  2. Donoho, D. et al. (2009), Reproducible research in computational harmonic analysis, Comp. Sci. Eng. 11(1):8–18, doi: 10.1109/MCSE.2009.15
  3. Reproducible Research, by the Yale Law School Roundtable on Data and Code Sharing, Comp. Sci. Eng. 12(5): 8–13 (Sept.-Oct. 2010), doi:10.1109/mcse.2010.113
  4. Peng, R. D. (2011), Reproducible research in computational science, Science 334(6060): 1226–1227, doi: 10.1126/science.1213847
  5. Diethelm, Kai (2012) The limits of reproducibility in numerical simulation, Comp. Sci. Eng. 14(1): 64-72, doi: 10.1109/MCSE.2011.21
  6. Setting the default to reproducible (2013), ICERM report of the Workshop on Reproducibility in Computational and Experimental Mathematics (Providence, Dec. 10-14, 2012), Stodden et al. (eds.), // report PDF
  7. Sandve, G. K. et al. (2013), Ten simple rules for reproducible computational research, PLOS Comp. Bio. (editorial), Vol. 9(10):1–4, doi: 10.1371/journal.pcbi.1003285
  8. Leek, J. and Peng, R (2015), Opinion: Reproducible research can still be wrong: Adopting a prevention approach, PNAS 112(6):1645–1646, doi: 10.1073/pnas.1421412111
  9. M. Liberman, “Replicability vs. reproducibility — or is it the other way around?,” Oct. 2015,
  10. Goodman, S. N., Fanelli, D., & Ioannidis, J. P. (2016). What does research reproducibility mean? Science Translational Medicine 8(341), 341ps12-341ps12, doi: 10.1126/scitranslmed.aaf5027

Schwab et al. (2000) report on the pioneering example of reproducible research in the Claerbout lab (Exploration Geophysics, Stanford University). The first public communication of this group’s approach that we could find goes back to 1992 [1]. That paper describes tools and processes in more detail, but for the same reason it is quite dated. So, we start with the summary account in CiSE. The Claerbout group developed an automatic build system for their published papers, including all the analyses and figures plus the typeset document. They used GNU make, certain standardized commands (burn, build, view, clean), and a notion of the file set or research compendium associated with the paper (data sets, programs, scripts, parameter files, makefiles). They report having used the system to-date for 14 papers involving 15 authors and hundreds of files. It’s remarkable to read about their careful methods for reproducible documents, given that more than two decades later we’re still struggling to adopt similar standards more widely.

Jump to Donoho et al. (2009). This could be the first group to explicitly associate reproducible research with open code and data:

Reproducible computational research, in which all details of computations—code and data—are made conveniently available to others, is a necessary response to [the credibility] crisis.

Donoho et al. admonish that computation cannot claim to be the third branch of science because most computational results cannot be verified. In the two traditional branches, standards of practice already exist for managing the ubiquity of error: deductive science uses formal logic and the mathematical proof, while empirical science uses statistical hypothesis testing and detailed methods reporting. “Many users of scientific computing aren’t even trying to follow a systematic, rigorous discipline that would in principle allow others to verify the claims they make.” Ouch!

Donoho et al. cite strong influences from Claerbout’s methods, and lament that these are still not widely practiced. This paper also repeats the classic paraphrase of Claerbout: “an article about computational science … is not the scholarship itself, it’s merely scholarship advertisement. The actual scholarship is the complete software development environment and the complete set of instructions which generated the figures.” (First appearing in a 1995 paper from this group [2].) My favorite quote from Donoho et al. (2009) is: “… if everyone on a research team knows that everything they do is going to someday be published for reproducibility, they’ll behave differently from day one.” The middle sections of the paper describe the various computational libraries developed to date in the Donoho group; those sections can be skimmed according to the reader’s interest. Towards the end, an interesting passage—written in the format of a Q&A—addresses the typical objections of researchers to working reproducibly. Many such objections are still hot topics today: it takes time and effort, we get no credit for it, competition, and so on. Notably, the final hypothetical objection is that “true reproducibility” should mean starting from scratch to re-create the results (rather than from the author-provided code and data). The rebuttal: “…it proves nothing if your implementation fails to give my results because we won’t know why it fails. The only way we’d ever get to the bottom of such a discrepancy is if we both worked reproducibly…"

The jointly authored paper of the Yale Law Roundtable participants (CiSE, 2010) expanded on the theme of transparency via open code and data. They defined reproducible computational research unambiguously as that making available all details (code and data) of the computations. Their additional recommendations include: assigning a unique identifier to every version of the data and code, describing within each publication the computing environment used, using open licenses and non-proprietary formats, and publishing under open-access conditions (or posting pre-prints). The rationale behind linking open access with reproducibility was absent, and some have criticized this aspect of the Roundtable recommendations. It may have grown out of the idea in Donoho et al. (2009) that “reproducibility means publication over the Internet,” and that authors should maintain a Web presence to facilitate discovery and access to their research. The connection between reproducible research and open-access publishing is, however, questionable. On the other hand, open code and data are valid components of reproducible computational research. Among future goals, the Yale Roundtable recognized the importance of enabling citation of code and data, of developing tools to facilitate versioning, testing and tracking, and of standardizing various aspects like terminology, ownership, policy.

Peng (2011) introduced the idea of a reproducibility spectrum. He says that reproducible research is a “minimum standard for judging scientific claims when full independent replication of a study is not possible.” Here we find an explicit distinction in terminology—something that continues to muddle the field—where full replication of a study involves collecting new data, with a different method (and code), and arriving at the same or equivalent final findings. (The distinction previously appeared in [3]) Peng mentions the Sloan Digital Sky Survey as an example of a project that would require formidable resources to fully replicate, and therefore proposes that reproducibility is a lesser standard that is more attainable. Other domains exist where full replication is unrealistic or extremely expensive. Reproducibility, says Peng, “falls short of full replication because the same data are analyzed again.” Nevertheless, it is a desirable minimum standard to assess the quality of the scientific claims. It requires that “the data and the computer code used to analyze the data be made available to others.” But, Peng laments, “the biggest barrier to reproducible research is the lack of a deeply ingrained culture that simply requires reproducibility for all scientific claims.”

Number 5 on our list (ordered chronologically) shifts to a different concern: numerical reproducibility in computations that involve parallel processing. In the discussion up until now, the concept of reproducible research assumed that running the same code twice with identical input will produce the same output. If the computation is done in serial, this assumption is good; but with parallel computing, it is not always the case. Diethelm (2012) ran an experiment using an application of finite-element analysis in computational mechanics. Executing the same simulation (same code, same input data) with varying number of processors gave different results! Investigating the differences and the source code pinpointed the cause of non-deterministic behavior: a direct solver for sparse linear systems (an external library). Diethelm goes through an example that illustrates how this can happen: a vector dot-product, computed in parallel over several partial sums. On each execution, individual processors may complete their portion of the sum in different order. In finite precision, addition is not associative and the final sum depends on the order of the partial sums. Under these conditions, ensuring numerical reproducibility involves introducing artificial synchronization points in the program, at the cost of additional run time. More elaborate techniques are available, but the conclusion is that in high-performance computing “lack of reproducibility is typically a price that must be paid for speeding up the algorithm.”

The ICERM Workshop Report (2013) builds on the contributions of the Yale Roundtable by placing particular focus on: (1) changing the culture and reward structure; (2) role of funding agencies, journals and employers; (3) teaching the skills for reproducible research. The required culture change includes valuing openness and transparency. But the academic reward structure sets critical barriers: “The current system, which places a great deal of emphasis on the number of journal publications and virtually none on reproducibility …penalizes authors who spend extra time on a publication.” Moreover, software development and data management are not valued scientific activities. The report addresses several ways to introduce incentives, requiring leadership from funders, journals and employers. Many of those discussions continue to this day in different venues (workshops, journal editorials, blogs, etc.).

I should add that I participated in the ICERM Workshop, giving a short talk titled “Reproducibility PI Manifesto.” The slides of this talk have been widely shared and commented [4].

Sandve et al. (2013) give us ten concrete actions we can take to make our research reproducible:

  1. For every result, keep track of how it was produced
  2. Avoid manual data-manipulation steps
  3. Archive the exact versions of all external programs used
  4. Version-control all custom scripts
  5. Record all intermediate results, when possible in standard formats
  6. For analyses that include randomness, note underlying random seeds
  7. Always store raw data behind plots
  8. Generate hierarchical analysis output, allowing layers of increasing detail to be inspected
  9. Connect textual statements to underlying results
  10. Provide public access to scripts, runs, and results

Some common threads run through most of these recommendations. First, recognizing that a final result is the product of a sequence of intermediate steps (the analysis workflow), a key device for reproducibility is automation. Second, the central technology for dealing with software as a living, changing thing, is version control. And finally, archive and document everything with the best tools at hand. The one, inescapable corollary for the purposes of training researchers is that command-line skills are essential.

Item 8 of our reading list (Leek and Peng, 2015) expands on the purpose of reproducible research: to protect the integrity of science and build the public’s trust on scientific results. Although a reproducible study can still suffer from poor study design, missing data, or confounding factors, reproducibility increases the rate at which we can uncover these flaws. Even so, the key is prevention via the training of more people on techniques for data analysis. Leek and Peng contribute to this goal via their massive online courses, and they also recognize the value of crowd-sourced workshops like Software Carpentry and Data Carpentry.

Next on the list is an essay by Mark Liberman, Christopher H. Browne Distinguished Professor of Linguistics at the University of Pennsylvania. He teaches introductory linguistics, as well as big data in linguistics, and computational analysis and modeling of biological signals and systems (among other topics). The subject of his essay is the big confusion of terminology that has spread on the reproducibility literature. He traces the confusion to a machine-learning workshop contribution, where the terms reproducible and replicable are swapped completely, compared to previous papers. Liberman concludes: Since the technical term ‘reproducible research’ has been in use since 1990, and the technical distinction between reproducible and replicable at least since 2006, we should reject [the] attempt to re-coin technical terms reproducible and replicable in senses that assign the terms to concepts nearly opposite to those used in the definitions by Claerbout, Peng and others.”

Our final item on the reading list is from earlier this year. Goodman et al. (2016) note that the various terms used in the field (e.g., reproducible vs. replicable) are not standardized. The importance of corroborating a previous study’s results is widely recognized. But, the authors note, “ … the modern use of ‘reproducible research’ was originally applied not to corroboration, but to transparency, with application in the computational sciences. Computer scientist [mistake: geophysicist] Jon Claerbout coined the term and associated it with a software platform and set of procedures that permit the reader of a paper to see the entire processing trail from the raw data and code to figures and tables. …This concept has been [used in] epidemiology, computational biology, economics and clinical trials…” [references provided]. Goodman et al. uphold the Claerbout/Donoho/Peng terminology, but propose a new lexicon as a way out of the confusion reigning the literature: methods reproducibility (original meaning of reproducibility), results reproducibility (previously called replication), and inferential reproducibility. Who knows if this new lexicon will stick, but what I like of this paper is its skillful discussion of differences among scientific domains that affect how each addresses reproducibility. In computational research, we’re used to a degree of determinism, for example, so methods reproducibility and results reproducibility are linked. Other fields have to deal with major stochastic variability. For most computational scientists, the second half of this paper will be alien, because it focuses on issues of statistical significance testing, clinical and pre-clinical research, and so on. It is good, however, to get a glimpse into this other world of science, where p-hacking and HARKing (hypothesis after results are known) are a thing.

Additional References

[1] Claerbout, Jon and Martin Karrenbach (1992). Electronic documents give reproducible research a new meaning, Proc. 62nd Ann. Int. Meeting of the Soc. of Exploration Geophysics, pp. 601-604, doi: 10.1190/1.1822162

[2] Buckheit, J. B. and D. Donoho (1995), WaveLab and reproducible research, In Wavelets and Statistics, edited by A. Antoniadis and G. Oppenheim, Lecture Notes in Statistics 103: pp. 55–81, doi: 10.1007/978-1-4612-2544-7_5

[3] Roger D. Peng, Francesca Dominici and Scott L. Zeger (2006), Reproducible epidemiologic research, Am. J. Epidemiol. 163 (9): 783-789. doi: 10.1093/aje/kwj093,

[4] Barba, Lorena A. (2012): Reproducibility PI Manifesto. figshare, doi: 10.6084/m9.figshare.104539.v1

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406 days ago
Oh this is great... I'm totally going to "borrow" this.
Corvallis, OR
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10/19/16 PHD comic: 'Abstract Art'

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Piled Higher & Deeper by Jorge Cham
Click on the title below to read the comic
title: "Abstract Art" - originally published 10/19/2016

For the latest news in PHD Comics, CLICK HERE!

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418 days ago
It's funny, I got this exact advice from my advisor during grad school. "The content can always be changed later"...
Corvallis, OR
417 days ago
Be sure to smudge your sigma
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Academic Trax: Episode 18

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In Episode 18, Kyle Niemeyer, Assistant Professor of Mechanical Engineering at Oregon State University, joins Jon again to discuss the graduate student union at OSU. We delve into more labor relations and how the administration rules impact academia. Kyle shares how OSU cannot really hire postdocs and discusses some items that are part of the student collective bargaining agreement. Kyle’s research website can be found here and he is also on twitter @kyleniemeyer.

Let us know what you think. We can be reached at or via email at Jon can be reached on twitter @profgears.

If you like Academic Trax, please leave us a comment on our website and also on iTunes.
Academic Trax Podcast Link

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522 days ago
It's me!
Corvallis, OR
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