saraConnor

Recently, my ex-advisor (I switched labs) sent me a manuscript that I am listed as second author on. I haven't been given any information about this manuscript until the document was sent to me. I was asked to do specific formatting and to make "any edits that [you] think would improve the paper." The manuscript was sent to me entirely written, which also means the part that is my area of focus in the manuscript was already written. I'm really not sure how to add anything in the paper when the part that I would play a role in has already been entirely fleshed out. My main concern here is that this ex-advisor will try to say that I didn't contribute to the paper - but I really haven't been given the opportunity to contribute to the paper at all because I was never looped into the development or writing process of the paper. Does anyone have an recommendations or advice for this type of situation? Thank you!!

Thanks for the comment @CAVALE. Acting class sounds interesting! Maybe something fun for the future. After some time has passed, I definitely think this comment is a product of this particular person and/or the fact that we present via Teams and everyone has their cameras turned off. The remark was made by my phd advisor and they have a reputation for making these kind of remarks to faculty and students. They literally told a fellow graduate student that they were boring. I also know they have gotten in trouble with another faculty member in the past (official reasons undisclosed). Unfortunately, I was not told any of this until after I accepted and started the program (after I accepted the offer their only 2 other grads dropped out without finishing their MS). Anyways, taking no action until evaluations are finalized is a good idea. I'm also hoping to pivot my research to work with other faculty (this has been working in my favor). A part of me wants to report this person because of their reputation for doing these things. But another part of me is just like, "keep cool and work with someone else" and avoid any form of backlash. Ugh. Anyways, thanks again for taking the time to comment and provide support.

Thanks for the follow up @PsyDuck90. Yeah, that's what I thought. And apart of me started thinking, "am I just getting offended," but the more I think about this it just feels like criticizing my personality. I also know that while I was presenting I was being mindful of trying to speak more "excited" (hence using the hand gestures like a conductor would) because she's made this comments before - that my voice sounds flat and unexcited. Apart of me wanted to lash out and say, "you sound like you have a frog in your throat!" Of course I would never do this, but I think you get my point. I get feedback like this from this person often, and it's starting to really wear on me - not really sure what to do about it.

Yes, I completely agree that feedback is important! @PsyDuck90 It was clear based on the other graduate students and faculty that I did effectively communicate my findings and several told me that I gave a great talk. My advisor spent less than two sentences on this point, and went on and on about how my voice sounded when presenting. Her criticism wasn't about improving my talk, it was about how my voice sounded to her -- which I find ironic because she has a nasally voice and doesn't enunciate her words very well. I do not see how criticizing the sound of my voice has anything to do with explaining my research (which I clearly was able to do given the positive feedback from others).

Recently, I gave my first research talk covering 7 different experiments that were all related. I created a visually pleasing presentation along with an interesting and informative dialogue. When I have to give a talk, I typically write a script that I use to practice and then have notes during the talk as a safety blanket. Since we are doing everything online, I used my hands a lot while I was talking (kind of like a conductor) to make sure to not sound too flat. Many of the findings in the talk were redundant, because the overall pattern of results were the same for all 7 experiments. Anyways, several grads and some professors reached out afterwards telling me that I gave a nice talk and the talk itself spurred on some discussion (which usually doesn't happen in brownbag). During lab meeting the week after my talk, my advisor spent most of the time talking about how my voice sounded during the talk. That it wasn't good enough, that I didn't excite the audience members, and just on and on about my voice. I find this entirely inappropriate feedback and simply not important - I'm not an actor/performer. Is this inappropriate feedback or is this what I should expect from an advisor?

We all know that placement into academic positions is highly competitive, much like most of the job market in general. Ultimately, my goal is to end up at a university where I can continue to conduct research and teach. I have been told that getting a job at a R1 institution is statistically unlikely and that you would have to dedicate 60 hours a week alone on research as a graduate student (this time would not include reading, classes, meetings, etc. according to the person who told me this). Are these realistic claims? What is the reality around R1 jobs outside of the fact that they are competitive? Is this the same for R2 institutions? Is it just as hard to land a R2 job? Any insights would be appreciated! Thank you so much for your time.

Thank you for the replies. Do either of you have any advice for getting feedback from an advisor? My advisor has told me to send sections of the draft (i.e., intro, results, discussion) as I write them. However, they have never read or provided feedback on any of these drafts (I've send the results twice and the intro once). From my understanding, an advisor is suppose to read and provide feedback on drafts but that is something that I am not getting. Thank you again!

Hello! I am a going into my second year as a PhD student in Cog Psyc. I have been working on two papers that I am the first author on. What is the typical experience for one's first publication as first author with their advisor? What is the typically workload break down? To what extent is/should the advisor be involved? Also, I know this is relative to the individual. I am speaking generally and more along the lines of what is typical. Any feedback would be wonderful! Thank you so much for your time. Be well, -SC

Thanks NK! Chunking/clustering is an interesting point that I am aware of but hadn't thought about in relation to my work! Hopefully I"ll get to talk more with my peers in the fall when things try to go back to normal. Unfortunately, my PI switched to this area of research recently, so they are very new to the area which makes it hard to discuss in depth.

Hello! I am a first year phd student in a Cog Psyc program. I know this isn't in the biology department, but humans are biological beings so I thought that gaining some insight from some biology grads would be very valuable. My research focus is in the area of ensemble perception -- which is our visual systems amazing ability to accurately and efficiently compute the mean of a set of similar objects. For example, if you are presented with a display of circles varying in size and asked what the average size of the circles are, you will estimate the mean very accurately! This is also referred to as summary statistics. My research focuses on the perception of variability. Through a series of experiments where I present a sequential set of 9 objects (different line orientations for one experiment), I have found a consistent bias to overestimate objects when they are more similar to each other (they vary by 1 degree) compared to when they are different from each other (they vary by 5 degrees). For example, if participants see a set of 9 lines that all vary within a range of 1 degree (low variability), they overestimate the variability in those lines by 55% where as they are pretty good at estimating the variability when the lines vary by 6 degrees (high variability). I have thought that maybe people are relying on the first few items or the last few items in a set to make their estimates, but I don't find this when I run the analysis. I also don't really find that they are using a specific group of lines to make their estimates. It also doesn't seem like they are using a range heuristic to make their estimates. That is, taking the largest and smallest of the set to estimate the variability. One thing that I have been thinking about is that we overestimate things that are more similar so that we are able to notices those subtle differences. For example, imagine that you are in the rainforest where there are various shades of greens and browns, meaning that there would be a lot of variability in the colors of greens and browns. It would be more advantageous if you were able to overestimate the variability in greens when they are mostly similar because this would allow you to detect some prey or a predator. My issue with this proposal is that I don't know how to make this into a testable mechanism or theory to explain why we overestimate the variability in objects that are similar. Mostly because I'm not in evolutionary psychology. I am in a vision lab, where we use psychophysics methodologies. I haven't found any clear literature that hones in on why people may be biased to overestimate a sequentially presented group of objects (that is, objects that are presented one at a time) that are more similar to each other. Are there any fellow grads (maybe even psychophysicists) out there who may have a plausible mechanisms (neural, statistical, etc) that may explain this? Any help brainstorming would be amazing! Thank you for your time and interest.

Do you mean that it is easier to overestimate similarities because we notice differences more than we do when things are similar? I think that could be possible. One thing that I have been thinking about is that we overestimate things that are more similar so that we are able to notices those subtle differences. For example, imagine that you are in the rainforest where there are various shades of greens and browns, meaning that there would be a lot of variability in the colors of greens and browns. It would be more advantageous if you were able to overestimate the variability in greens when they are mostly similar because this would allow you to detect some prey or a predator. My issue with this proposal is that I don't know how to make this into a testable mechanism or theory to explain why we overestimate the variability in objects that are similar. Mostly because I'm not in evolutionary psychology. I am in a vision lab, where we use psychophysics methodologies.

Hello! I am a first year phd student in a Cog Psyc program. My research focus is in the area of ensemble perception -- which is our visual systems amazing ability to accurately and efficiently compute the mean of a set of similar objects. For example, if you are presented with a display of circles varying in size and asked what the average size of the circles are, you will estimate the mean very accurately! This is also referred to as summary statistics. My research focuses on the perception of variability. Through a series of experiments where I present a sequential set of 9 objects (different line orientations for one experiment), I have found a consistent bias to overestimate objects when they are more similar to each other (they vary by 1 degree) compared to when they are different from each other (they vary by 5 degrees). For example, if participants see a set of 9 lines that all vary within a range of 1 degree (low variability), they overestimate the variability in those lines by 55% where as they are pretty good at estimating the variability when the lines vary by 6 degrees (high variability). I have thought that maybe people are relying on the first few items or the last few items in a set to make their estimates, but I don't find this when I run the analysis. I also don't really find that they are using a specific group of lines to make their estimates. It also doesn't seem like they are using a range heuristic to make their estimates. That is, taking the largest and smallest of the set to estimate the variability. I haven't found any clear literature that hones in on why people may be biased to overestimate a sequentially presented group of objects (that is, objects that are presented one at a time) that are more similar to each other. Are there any fellow cog psyc (maybe even psychophysicists) out there who may have a plausible mechanisms that may explain this? Any help brainstorming would be amazing!