This is the webpage for section 3 of the Dartmouth Graduate Ethics Seminar (UNSG 100).
I will collect links to documents, case studies, and readings for the course on this page. **We will
meet Monday evenings from 4-6 pm in Kemeny 201 on 9/18, 10/2, 10/16, and 10/30.**
The seminar will be based on group discussions, case studies, and collaborative activities focused on developing skills and learning about resources for ethical problem solving.

Since I am a mathematician, this section will deal specifically with topics of interest to math graduate students such as qualifying exams, advisor selection, mathematical research, and teaching undergraduate courses. One purpose of the course is to help acclimate you to the community of professional mathematicians - both researchers and teachers - and explain some of the aspects of academia that differ from other professional environments. Mathematics students are strongly encouraged to read the graduate handbook and be familiar with the department policies and resources on the website. The FAQ in particular has lots of helpful information. Finally, the introductory chapters of the Written Qual Book are well worth reading.

## Week 1: Professionalism

### Lesson Plan

We will begin with an introduction to the goals and purposes of the seminar and a brief discussion of ethical frameworks for decision making. As an application of these methods we will consider some short case studies about professional behavior in the university environment. Following this introduction, we will look at an overview of the the mathematical research community through the lens of ethical guidelines prepared by national organizations:

- AMS Code of Conduct
- AMS Ethical Guidelines
- MAA Code of Ethics
- ACM Code of Ethics and Professional Conduct
- AAUP Statement on Professional Ethics

We will also consider the role of scholars and professors in society at large. This topic is particularly relevant in light of the funding cutbacks that many universities are experiencing and the ensuing public discourse over the future of higher education. For many mathematicians, the answer to this question has changed a great deal since G. H. Hardy wrote his book ``A mathematician's apology.'' More reflective of current academic standards, UGA Geology professor Dr. Bruce Railsback has collected an interesting list of non-lecturing job duties of university professors that are rarely considered in public debates about the ``usefulness'' of higher education. Similarly, the AMS has collected a set of resources adressing the question: ``What do mathematicians do?'' We will use these documents, together with press articles on the topic (like these polemical opinion pieces from the New York Times) and stackexchange posts (like these two from MathOverflow or these two from Academia) as a starting point for a discussion of our responsibilities as scholars.

The case studies and role plays for this week focus on issues of professional behavior, both in the classroom and as researchers. The source documents can be found at:- Case Study: Humor, Motivation, and Humiliation by A. Donovan (on Canvas)
- Case Studies: The Professoriate #2,3,4,7,8 by J. Van Patten (Higher Education Culture: Case Studies for a New Century (via ERIC))
- Case Study: Career Dreams Up in Smoke (ORI RCR Casebook)
- Role Play: The Sad Truth (ORI RCR Casebook)

## Week 2: Mentorship

### Lesson Plan

#### Background Materials

Until recently, there were very few resources dedicated towards helping students develop effective metoring relationships in graduate school. That is starting to change, as universities and individual departments are beginning to realize the importance of encouraging positive mentoring experiences for their students and faculty. Many of these groups have developed (occasionally quite extensive) guides to all aspects of the mentoring process for both students and faculty members. Although we do not have time in the seminar to discuss all of these works individually, the links collected here represent excellent sources for expanded reading:

- University of Michigan
- Council of Graduate Schools
- University of Nebraska
- Harvard Medical School
- University of Pittsburgh
- Northwestern University

In addition to the resources above there are also books dealing with these issues. Much of the Dartmouth syllabus on mentoring is based on two books: Scientific Integrity by Francis Macrina and Getting Mentored in Gradute School by Brad Johnson and Jennifer Huwe. On Being a Scientist by the Committee on Science, Engineering, and Public Policy also covers some of these topcis. Finally, I have always been a fan of Ian Stewart's Letters to a Young Mathematician and the wonderful mentoring examples that it contains. I have copies of these books that you can borrow if you are interested in reading more.

Ben Barres also has a recent paper on these topics How to pick a graduate advisor published in Neuron (2013). This paper also highlights the problems that occur when bibliometrics are applied across fields. This is an ethical issue in its own right, although possibly not one we will have time to discuss this week. Also, although the standard advice about listening to strangers on the internet applies, you can get an idea of some cultural norms and diverse perspectives on mentoring by browsing the advisor tag at the Academia Stackexchange.

Another good source of advice comes fom documents intended for advisors rather than advisees. Particularly in our setting, these documents offer both perspective on how advisors approach mentoring relationships with students as well as advice that may be useful as you begin to mentor other students yourself. The University of Michigan, University of Rhode Island, and Indiana University have created guides for this purpose. Additionally, the links and aswers to this question are quite insightful and offer a mathematician's perspective.

#### Seminar Outline

In the seminar itself, we will talk about some of the basic issues involved in selecting and interacting with a variety of mentors. Case studies and source documents, such as lab contracts and advising guidelines, will help provide some context and examples of real-life mentoring situations, some of which have ethical implications. Overall, the focus of this week leans towards practical aspects of the mentorship process but we will debate some common dilemmas that can arise. Our discussion will mainly be guided by trying to answer the following questions:

- What is a mentor?
- Who can be a mentor
- How can you find a mentor?
- What does/should/can a mentor do?
- How can you get the most out of your mentoring experiences?
- What if something goes wrong?

We will also look at some example lab contracts to examine the different types of expectations between graduate students and their mentors. In mathematics, we rarely resort to formal documentation of mentoring rights and responsibilities but it is still good to think about what such a document might contain. Here are some links to the contracts we will analyze:

- Louisiana State University
- University of Connecticut
- Virginia Tech
- University of Wisconsin
- Texas A&M

Although much of the previous discussion is quite general and applies to a wide variety of departments and situations, there are some aspects of this topic that are specific to mathematicians and the Dartmouth math department in particular. A couple of Mathematics professors have put guides on-line describing their mentoring styles and expectations: Fan Chung, Allen Knutson, and Ravi Vakil. Additionally, a slightly stylized document from Dartmouth Mathematics Professors can be found here.

#### Dartmouth Math Department

In the Ph.D. program at Dartmouth you will have many opportunities for mentoring, both formal and informal. Between your first year advisor, your primary and secondary thesis advisors, your teaching mentor, the advisor to graduate students, and the graduate representative there are plenty of faculty members directly invested in your success. Additionally, most faculty members are happy to discuss mathematics or your progress through the program. You should take advantage of as many of these opportunities as possible particularly as you are trying to find a thesis advisor.

I don't feel that I can improve on the commentary already written by Tom Shemanske in Section 3 of the Graduate Handbook and Section 1 of Mark Tomforde's Guide (you should read both!) but I would like to reinforce a few of things:

- Remember that not all mentorships are formal advisor relationships; finding a faculty member you feel comfortable talking to can make a real difference.
- Make good use of your qualifying exam committees and course instructors. You should meet with your committees regularly and attend office hours whenever you can.
- Spend some time talking with graduate students who are further along in the program than you are, including current and former students of your potential advisors. They can provide much needed context and give insight into about what it is actually like to work with a particular professor.

## Week 3: Authorship

### Lesson Plan

#### Background Materials

The ethical and cultural norms of mathematical publishing are quite distinct from the other STEM fields. The AMS has published several statements describing some of these differences. Most relevant to the topic of authorship are the statements on publication rates, joint research, and citations and impact. This final topic is related to a subject (bibliometrics and altmetrics) that I have studied a great deal. In general, I am quite skeptical of applications of these methods to mathematicians and mathematical journals.

These two (link1 link2) excellent questions on MathOverflow are a great place to start reading to get some context and information on how mathematicians think about authorship. Several of the answers (as well as Fan Chung's excellent advice on collaboration) reference the hyperbolically stated Hardy-Littlewood rules which have provided the basis for much mathematical thought about collaboration, although there is some debate as to the ethical nature of these axioms.

Most of the sciences have adopted standards similar to the Vancouver Protocols with regards to publication practices. Examples include the ACS, APS, and AAAS among many others. The ICMJE has formulated a four pronged test for determining paper authorship that many journals have adopted or modified:

- Substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data for the work.
- Drafting the work or revising it critically for important intellectual content.
- Final approval of the version to be published.
- Agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

#### Seminar Outline

Authorship is not necessarily a pressing concern for mathematics Ph.D. students, as many mathematics students graduate without ever having published a paper. In fact, every year several of our students obtain great jobs (including tenure-track professorships) without having published. However, it is nice to start thinking about some of these issues well in advance of needing to apply them. In our discussion section this week, we will focus on the following issues related to publications:

- Why do we publish papers?
- Why do mathematicians use the ArXiv?
- Who should be an author on a paper
- What order should the authors be listed in?
- How do bibliometrics work?
- How does peer review work?
- What is a conflict of interest?
- What is plagiarism?
- What is the difference between plagiarism and copyright infringement?

#### Case Studies

The case studies this week will be mostly drawn from recent real life examples of unusual publication situations. The Committee on Publication Ethics (COPE) collects descriptions of the more than 500 cases that have appeared before their committee since 1997. Similarly, Retraction Watch has been providing daily journalistic reports on ethical issues in science publication since 2010.

## Week 4: Intellectual Property in Academia

### Lesson Plan

For the final week of the seminar we will focus on data collection and copyright issues. Data collection and image manipulation do not tend to be central issues in mathematical research but Intellectual property issues are a more universal academic concern. Dartmouth's policy on Data Retention hosted by the Office of Sponsored Projects is a good place to start reading about data ownership at Dartmouth.

Copyright assignment at Dartmouth is discussed under the Office of Sponsored Projects Copyright Ownership Policy as well as the Dartmouth Copyright Policy & Guidelines and the newly updated Dartmouth College Policy on Patents, Copyrights and Other Intellectual Property Rights created by the Technology Transfer Office. Dartmouth Librarian Barbara DeFelice is very knowledgeable about issues of copyright in academia.

Many questions about the use of copyright protected materials in the educational setting relate to fair use. This is a legal framework that consider four elements: purpose of the use, nature of the original work, amount of work used, and commercial implication, that determine whether a portion of a previous work may be used without explicit permission from its creator. The US Copyright Office maintains an index of fair use related judicial decisions. Stanford also maintains a list of summaries of fair use cases.