Welcome to the Cognitive Epistemology Lab in the Department of Psychology at UC Berkeley! We’re excited to have you on board. We’ll do what we can to help you accomplish your research and career goals, acquire new skills, and we hope that you’ll enjoy doing science with us.
Every lab member is expected to read this manual in full upon or prior to joining. This lab manual was inspired by and adopts heavily from other lab manuals (e.g., from Mariam Aly’s lab manual). It’s also a work in progress. If you have ideas about things to add, talk to me (Marina, the PI). This manual is licensed under a Creative Commons Attribution - NonCommercial 4.0 International License. If you’re a PI or a trainee in a different lab and want to write your own lab manual, feel free to take inspiration from this one:)
General Philosophy
This lab studies how learning about the world can happen, which means our own practices are what we constantly reflect on. The principles below are not fixed rules, but evolving commitments. We are actively trying to learn what discovery is and how it can be facilitated, and this will likely change how we do our own studies in the future.
A. Science
We try our best to learn about the world, yet there is no single recipe or “right” way of doing science. In fact, we are still learning how to ensure science is a successful learning activity. This means we must critically examine our methodological choices (e.g., experimental design, analyses) in light of the specific context of a study and be transparent about the assumptions we are making. (In science, we always make assumptions.) As long as we are transparent about our choices, others can see what we’ve done and evaluate the credibility of our inferences.
We try to ask big questions and make progress in areas that are not well understood. Taking on new questions, rather than making slight improvements over what has already been done, often means dealing with more uncertainty and having to do more groundwork, but we think this kind of science is more meaningful and generative. This lab is supportive of ambitious projects, and we aim to help you navigate the practical side of science while trying to do something new or challenging.
Science is not linear. We learn best if we also engage with things that are not immediately associated with deliverable outcomes (e.g., see Stanley & Lehman, 2015). This includes 1) engaging with talks not directly related to your main interests, 2) exchanging ideas with colleagues that do not immediately transform into a project, 3) reading literature outside of your immediate area of interest. These activities help us become more creative and broad thinkers who can eventually come up with new perspectives on the cognitive phenomena.
It is okay to make mistakes. Mistakes in science are expected (many have argued that science works through mistakes; e.g., see this). If you make a mistake, please notify your collaborators. Transparency is essential.
B. What this means for how we work together (applies both to PI and the trainees)
We are a community of scholars. This means that we work together, seek feedback from others and help our colleagues. Given A1, the PI believes that the best way for us to improve our work is to engage with other people. Lab members are encouraged to share their (even half-baked) ideas with other lab members or other scholars. The following are our expectations for lab members:
a. Be generous to others. Science works because people help each other. I expect lab members to be generous with their time, ideas, and feedback when others ask for their thoughts. Your generosity will come back to you.
b. Don’t be afraid to ask for feedback. This includes feedback from lab members and other colleagues in the department.
c. Whenever possible, work from the office. This helps create opportunities for spontaneous, productive interactions.
d. Each lab member is expected to lead at least one lab meeting per semester sharing the data, literature, thoughts that they are currently exploring. Other lab members are expected to contribute to all lab meeting discussions.
We take science seriously because we genuinely care about learning about the world. This means we value honesty, integrity, and intellectual responsibility. There is no place in this lab for cheating, fabrication, falsification, plagiarism, or any other practices that misrepresent what was actually done or found. We value open and transparent science and, whenever possible, aim to publicly share our code, data, and other supporting materials alongside our scientific reports.
We treat others with respect. This means assuming good intentions, being mindful of how your words and actions affect others, and recognizing that people come from different backgrounds, experiences, and constraints. Respect includes listening carefully, taking others’ ideas seriously, giving credit where it is due, and communicating disagreements in a constructive way.
We value reliability. Show up when you say you will, meet deadlines when possible, respond to emails in a timely manner, and be transparent when something goes wrong.
PI
My role as a PI is to support your research and career goals and to help you learn new things. I will do my best to do this through regular meetings, where I will provide timely and constructive feedback. I will be available to support you at all stages of the research process, including literature review, research design, data collection, analysis and interpretation, visualization, writing, and communicating results.
I will also ensure that you have the resources you need to do your work well. This includes computational resources (e.g., hours on a supercomputer cluster), funds for participant compensation, and support for conference travel so that you can present the work we've done together.
Beyond the research itself, I will do my best to promote you and your work, and to support your career development. This includes helping you apply for internships, fellowships, or jobs during or after your time in the lab. The lab will support you regardless of whether you are looking for academic or industry positions.
I believe mentorship is a two-way process. I will regularly invite you to give me feedback on my mentorship, and I promise to take that feedback seriously.
Trainees
Even though I, as your mentor, promise to support you to the best of my ability, you are ultimately responsible for your own research and educational outcomes (please, read this!). This means that while I will guide you, give feedback, provide resources, and help you navigate challenges, you are the one who drives your research forward by setting goals, following through on plans, asking questions, and taking ownership of your learning. My ultimate goal is to help you grow into an independent researcher. That involves increasing autonomy, decision-making, and responsibility over time.
Some practical things
Here are some things that may be useful to know as we work together.
Timelines. To help us plan realistically and produce work we are proud of, I have the following expectations:
a. Paper deadlines. If you plan to submit a paper to a conference or journal with a fixed deadline, the first full draft should be completed at least two weeks before the deadline. This gives us enough time to improve it together and arrive at a version we feel good about.
b. Presentations. If you present our work together, I expect to run through the final version of the poster/slides at one of our scheduled meetings before the presentation.
c. Recommendation letters. I require at least two weeks’ notice before a recommendation letter is due.
Authorship. As a general rule of thumb, for projects we work on together, I expect the leading student to be the first author and me to be the last author. Roles (e.g., leading vs. supportive) will be discussed at the outset of a project, but they may evolve as the project develops. The lead trainee has primary say in whether to invite new collaborators or co-authors, but this should always be discussed with the PI beforehand.
When working with others, discuss authorship expectations before making any assumptions or changes, and always include me (the PI) in these conversations. If an authorship dispute arises, I will discuss it with all parties and will be responsible for the final decision. But always remember: B1A! (i.e., be a good human first).
Submission approval. Whenever a project is submitted anywhere (e.g., to a journal, conference, preprint server), all coauthors must approve the submission beforehand. This includes agreement with the content, the authorship order, and the venue.
Project transfer. It is normal to abandon or pause the project if we get stuck or if the project does not lead anywhere productive. However, as a general rule of thumb, if we have already collected data, we aim to report the results in some form.
The PI reserves the right to suggest a prior project to a new trainee after a conversation with the original leading trainee if there has been no progress on the project for more than one year. In such cases, the original leading trainee will be included as a co-author, and authorship order will be discussed at the time of project transfer.
Conflict Resolution. Disagreements and misunderstandings are a normal part of collaborative work. If a conflict arises, the first step is to communicate openly and early. Many issues can be resolved simply by clarifying expectations or constraints.
If you feel uncomfortable raising a concern directly with the person involved, you should bring it up to me, the PI. I will take such concerns seriously and treat them with care and confidentiality. If your concern involves me and you are not comfortable discussing it with me directly, you should bring it to the Psychology Department’s Director of Graduate Studies.