r/PhdProductivity

I am applying to PhD studies in America, and I would really like to get accepted. I studied in English in Slovakia for both my bachelor's and master's degrees. I do not believe in my writing; to say this clearly, I am very insecure about it and would like to improve. This is my finished SOP, which I am planning to apply with any criticism and changes are welcome. I would really appreciate the help.

The cinematography scene has been a long-term fascination of mine. This spiraled into my fascination taking a different direction, which was observing a variety of texts and films and noticing the differences in adaptations. The specific instance my fixation grew was when I was introduced to the 1990 miniseries IT written by Stephen King. This occurred in my youth, and from an early age I noticed the differences between novels and adaptations, compelling me to research the topic further for my bachelor’s thesis on why these alterations were made. Comparing certain issues, arguments, topics, stories, and adaptations has become a strong suit of mine. Stephen King has explored recurring themes across literature, such as morality, racism, sexism, and domestic abuse, which led me to analyze these themes and the alterations that are essential within the novel but omitted in film form. Upon reflection, this inspired my bachelor’s topic, which is titled “A comparative study of Stephen King’s novel “It” and its various adaptations”. An important aspect within the comparative realm that I have noticed is that it can be compared to translation studies. The manner in which certain words cannot be directly translated into one language, simply because there is no equivalent in each language of translation. This furthered my research to observe why certain aspects cannot be translated correctly from written form to on-screen.

The theoretical framework orbited the mere exposure effect, which aligned perfectly with the main aims and arguments, which I strived to achieve in the bachelor’s thesis. Moreover, this meant arguing the fact that what the audience experiences first is ultimately the piece they shall favor due to being exposed to it first. This is a common issue when analyzing novel-to-film adaptations, since an audience usually experiences reading the written form first. Coincidentally, this argument was vital in my thesis, along with the translation argument concerning cinematography and how it can be analyzed from the translation perspective. The bachelor’s thesis attempts to argue the facts of time constraints, monetization, differences in perspectives, advancement of technology, and cultural time shifts, among others. Additionally, another crucial aspect that needs to be taken into consideration is the themes and symbolism that were necessary in the novel, which did not have the same effect on screen. The investigation on this topic closely relates to the source Linda Constanzo Cahir (2006) and her views on adaptation from her theory piece titled “Theory and Practical Approaches”. The arguments aided the bachelor’s thesis to thrive in the direction of proving the arguments put forward and the details that were important in the novels.  Along this journey, I have gained immense knowledge in this field and a plethora of information in adaptation studies, as well as comparative analysis and fundamental facts needed to further research any topics similar to my bachelor’s thesis.

I have grown to admire these topics and themes. Moreover, this inspired me to further immerse myself in similar themes for further research, since the comparative realm is so vast. To make my dissertation thrive, I believe it is essential to be guided by renowned scholars with profound knowledge in this field who can point me toward an advantageous trajectory. Professors such as David Greven, Mark Minett, and Susan Courtney have also inspired me in the past when I was writing my bachelor’s and master’s theses. Their topics align with my past research, especially since the focus of my master’s thesis was on the role of Nen (power system) in the well-known anime Hunter x Hunter. My curiosity grew while writing about this topic, observing it through the lens of narrative complexity, character identity, and worldbuilding. The challenges I faced while writing my master's thesis proved that conducting research is both demanding and rewarding; however, the experience also made me realize that my strengths lie in research and that I enjoy the process of writing and refining academic work.  The thirst for knowledge and improvement is essential in an academic setting, and I have realized that early; due to this fact, I always strive to improve.

My research direction incorporates themes of horror, narrative shift, the differences in writing and improvement in Stephen King’s It and The Shining, and the effects this had on the adaptation. Both pieces of literature are very different; however, similar in certain aspects. Additionally, my research plans consist of intermedial transposition, authorial intent vs. director autonomy, and cultural reception longevity. The main issue I have noticed and would like to argue is Stephen King’s writing and why there is a shift between The Shining and It, and why one piece stands out over time and receives multiple adaptations while The Shining is noticeably left in the shadow.  Highlighting the importance of the written piece when it concerns adaptations. Adding knowledge of different perspectives when it concerns a specific literary piece and the outcomes due to clashes in artistic view. Given that this is an emerging field with limited existing research, I would appreciate the opportunity for this dissertation to serve as a foundation for further scholarly investigation in this area, under the guidance of faculty at the University of South Carolina. I strongly believe that, if admitted to the University of South Carolina, I would have the opportunity to further develop my research under the guidance of distinguished faculty members, which would elevate my academic career and enable me to contribute meaningfully to the field of adaptation studies and comparative literature.

Is the first draft of their PhD thesis generated by AI? And apart from PhD thesis, are they (specifically STEM PhD Students) writing first drafts manuscripts for peer reviews using AI? And what about coursework-related papers and assignments - are they doing first drafts sing ChatGPT (or other similar LLM AIs)?

Hi everyone,
Quick question for people who do systematic reviews and meta-analyses.
Is there an all-in-one platform that covers the entire workflow, so you don’t have to switch between multiple tools?
If yes, which one? If not, what would you consider a fair monthly subscription price for a platform that does?

Hi everyone, and welcome!

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Just wanted to share the prompt I use when correcting grammar and writing with an LLM. Paste this into ChatGPT, Gemini, etc., followed by the passage of text.

>Rephrase the following text to improve clarity and correct any grammar or punctuation errors, while keeping the original meaning intact, do not add any external information or change the meaning, hedging, etc. maintain the level of abstraction, do not generalize, or provide concrete examples that doesn't appear already in the text below. If XXX appears, substitute it with a correct word or phrase, based on the context. Do not add interpretations, implications, or inferred meanings. Do not rephrase if not necessary, only rephrase if it improves clarity or corrects grammar or punctuation errors. If you'd like to offer additional suggestions, such as improvements to logic, additional information, or alternative interpretations, please do so in a postfix section in the end of the rephrased text you provide that keep the meaning intact, the added section should clearly be labeled as "Suggestions" or "Additional Information". The suggestions should be concise and relevant to the content of the text, presented as a list of numbered bullet points we can further discuss. Do not use em-dashes, clauses and semicolons, use comma and period instead. Aim to avoid using colons.

This lets you write much faster, think of what LaTeX did for formatting. You simply skip past any grammar mistake you know you've made. The revised text includes the fix, so you also get to learn from it.

Another tip, use medium thinking effort, which in my experience tend to produce better results. Higher thinking effort produce some over-edits.

I'm looking to restart my PhD research (last year has been...a drag to say the least) and I'm very overwhelmed with all the offerings for research AIs/LLMs. I'm not looking for something to speedrun through papers or come to conclusions itself, I want an AI that can help with deep research, can converse, doesn't hallucinate sources (although I always check) and is an all rounder, rather than just a paper finder.

I've seen Elicit, SciSpace and Consensus a lot. All of them have very similar pricing so their price isn't the point. I already have Perplexity pro from a promotion they did in Christmas, and my Google One trial sub is ending next month, but I am not currently paying for any AI.

I follow this guy Andy Stapleton on Youtube that regularly puts out AI related content for PhDs but he's pushing a new "workflow" (including new AIs) every week.

What are you using and what do you think of their strengths and shortcomings?

Academia has officially become an infinite while loop, and it's crashing our brains.

Looking at the stats lately, it’s wild how much happier PhD holders are in industry compared to academia. Has the ivory tower really gotten that toxic? Because it honestly feels like it.We invariably get stuck in this exhausting cycle, like a buggy Python while loop. The problem is, academia forgot to increment the wellbeing variable, so while stressful == True: just runs forever. There’s no break statement in sight, it's a total infinite loop, and it is actively crashing the brains of PhDs and scientists everywhere. Maybe I’m wrong, maybe I’m right—but it really feels like the system is just completely frying us right now.

For those who already hit Ctrl + C and executed a keyboard interrupt to escape to industry: is the grass actually greener, or does it just have a different set of bugs? And for everyone still stuck inside the loop—what is keeping your script running?

A part of the story I’m writing right now has a little town cult, think of itinerant preacher and deviated religion !
I wanna be very respectful and insist on the fact that’s it’s a fanatic cult, very far for the reality, but I find important to start from the right basics.
The only thing is that I lack ideas and precisions for bible icons or religious metaphors. Do you know any accurate website that could help me ? Once again I refuse to use gpt or any other for this and I also think it’s very important I have the true base before drifting to cult-like religion
Also let me know what you think could be interesting to check or search for this story !

As title says,
I am not code savvy, I have data. I know what I want but I am not good at writing code. I come from biological sciences background. I can do well with excel but not with coding. I know there are packages in python like Pandas, Matplotlib, Seaborn for data visualisation but I feel it has progressed much more than those packages. I kinda feel like I’m left behind and the world is way ahead. I am trying to accept that AI and ML has seeped into research even with biology and medicine. As much as I tried to run away from the coding, it has caught up with me. I have nothing against coders, it’s just that I am not well versed in it and I feel if I start learning now, it’s too late. So, I want to take help from AI to help me with it. My supervisor says use Codex but I am not satisfied with it somehow, I feel like it is not giving me what I want ( could totally be because of the way I ask questions too, ngl). So, if I have like a dataset and want AI to help me with coding, what is the best to use so that I don’t hate coding and also start appreciating it.

How do you use Claude and other tools in your research? What is acceptable and what isn’t? If you are a master’s or phd student please share your experience or any stories with us. I am starting my master’s thesis in ML soon so I want to know how to best use Claude and others. What is allowed and what isn’t in academic research. Please share any advice and recommendations.

Thanks.

For those who’ve served on PhD admissions committees: what’s one moment in an applicant’s materials (something they mentioned, an interview answer, a shared detail, an action, or anything) that made you think ‘this person will make a great grad student’? Curious what’s stayed with you from one of the best applicants you’ve ever reviewed.

Heyyy I’m a PhD student - just filed! 😩👏 - and just curious: How are people were/are keeping all their notes and PDFs organized and searchable while working on their dissertation for years?

Zotero, Evernote, and Obsidian just didn’t fully work for me. I’m also a digital humanities student, so I’m working on building a bare bones database that’s simple for this sort of work/research. Mine got completely overwhelming over the 5 years, so I’m trying to build something simple that would check all the boxes and make it easy for people to sift through all their material. Let me know what u were wishing was in the tools u used!

Hi everyone, 

I either want to be an animal scientist and/or start my own independent business creating oral bait machines for feral felines to prevent the spread of disease and other ailments within their colonies. My specific question for this post is, as the title says, how do modern researchers use AI tools in their current research field, and what are the pros and cons of using such tools against or with traditional methods?

For those who don’t know who I am, please visit my previous post: https://www.reddit.com/r/UndergraduateResearch/comments/1se3mb8/comment/otvcpsc/?utm_source=share&utm_medium=web3x&utm_name=web3xcss&utm_term=1&utm_content=share_button

I want this to be a civil, proper discussion and hope that researchers within the animal sciences fields and/or other researchers can help me gain more insights into this pretty contentious topic within the academic community. So sorry for the hassle.