The research group and the university, is an environment that must be free of harassment and discrimination. All lab members are expected to abide by the University of Texas at Austin policies on nondiscrimination and harassment.
The research group is committed to ensuring a safe, friendly, and accepting environment for everybody. We will not tolerate any verbal or physical harassment or discrimination on the basis of gender, gender identity and expression, sexual orientation, disability, physical appearance, body size, race, or religion. We will not tolerate intimidation, stalking, following, unwanted photography or video recording, sustained disruption of talks or other events, inappropriate physical contact, and unwelcome sexual attention. Finally, it should go without saying that lewd language and behavior have no place in the lab, including any lab outings.
If you notice someone being harassed, or are harassed yourself, tell Krishna immediately. If Krishna is the cause of your concern, then reach out to the department chair or another trusted faculty member in the department.
The Geoelements research group and UT Austin, is committed to ensuring research integrity, and we take a hard line on research misconduct. We will not tolerate fabrication, falsification, or plagiarism. Read UT Austin’s policies on the conduct of research carefully.
A big problem is why people feel the need to engage in misconduct in the first place, and that’s a discussion that we can have. If you are feeling pressured to succeed (publish a lot, publish in high impact journals), you should reach out to Krishna and we can talk about it – but this pressure is something we all face and is never an excuse to fabricate, falsify, or plagiarize. Also, think about the goal of science and why you are here: you’re here to arrive at the truth, to get as close as we can to facts about the brain and behavior. Avoid accidental plagarisms too, do not copy-paste sections from your previous papers or that of the group. Always write / describe in your own words. Use tools like turnitin or Grammarly to check for plagiarism. Not only is research misconduct doing you a disservice, it’s also a disservice to the field. And it risks your entire career. It is never right and never worth it. Don’t do it!
If you gave someone else your raw data, they should be able to reproduce your results exactly. This is critical, because if they can’t reproduce your results, it suggests that one (or both) of you has made errors in the analysis, and the results can’t be trusted. Reproducible research is an essential part of science, and an expectation for all projects in the lab.
For results to be reproducible, the analysis pipeline must be organized and well documented. To meet these goals, you should take extensive notes on each step of your analysis pipeline. This means writing down how you did things every step of the way (and the order that you did things), from any pre-processing of the data, to running models, to postprocessing analysis. It’s also worth mentioning that you should take detailed notes on your experimental design as well. Additionally, your code should also be commented, and commented clearly. We all know what it’s like to sit down, quickly write a bunch of code to run an analysis without taking time to comment it, and then having no idea what we did a few months down the road. Comment your code so that every step is understandable by an outsider. Finally, it is highly encouraged that you use some form of version control (e.g., Git in combination with GitHub) to keep track of what code changes you made and when you made them, as well as sharing code with others. The lab’s GitHub is https://github.com/geoelements.
Reproducibility is related to replicability, which refers to whether your results can be obtained again with a different data set. That is, if someone ran your analysis again, do they get the same results? If someone ran a conceptually similar study, do they get the same results? Science grows and builds on replicable results – one-off findings don’t mean anything. Our goal is to produce research that is both reproducible and replicable.
Like other labs, we will follow the APA guidelines with respect to authorship:
"Authorship credit should reflect the individual's contribution to the study. An author is considered anyone involved with initial research design, data collection and analysis, manuscript drafting, and final approval. However, the following do not necessarily qualify for authorship: providing funding or resources, mentorship, or contributing research but not helping with the publication itself. The primary author assumes responsibility for the publication, making sure that the data are accurate, that all deserving authors have been credited, that all authors have given their approval to the final draft; and handles responses to inquiries after the manuscript is published."
At the start of a new project, the student or post-doc taking on the lead role can expect to be first author (talk to Krishna about it if you aren’t sure). Krishna will typically be the last author, unless the project is primarily under the guidance of another PI and Krishna is involved as a secondary PI – then Krishna will be second to last and the main PI will be last. Students and post-docs who help over the course of the project may be added to the author list depending on their contribution, and their placement will be discussed with all parties involved in the paper. If a student or post-doc takes on a project but subsequently hands it off to another student or post-doc, they will most likely lose first-authorship to that student or post-doc, unless co-first-authorship is appropriate. All of these issues will be discussed openly, and you should feel free to bring them up if you are not sure of your authorship status or want to challenge it.
If a student or post-doc collects a dataset but does not completely analyze it or write it up within 1 year after the end of study, Krishna will re-assign the project (if appropriate) to another person to expedite publication. If a student or post-doc voluntarily relinquishes their rights to the project prior to the 1-year window, Krishna will also re-assign the project to another individual. This policy is here to prevent data from remaining unpublished, but is meant to give priority to the person who collected the data initially.