I'm not really sure what field I'm targeting, so I was hoping people would note their favorite open access journals and I could investigate (and I also thought a more generic list would be generally interesting to all the HN folk).
I don't mean to be harsh, but it's hard to see how your article is publishable in its current form.
An academic paper is a kind of conversation between experts. You need to describe the problem you're exploring, state what others have done in the area, and finally explain how you are contributing to the problem and show that your contribution is novel.
What you're writing about reads like a combination of philosophy and machine learning. The philosophy probably makes it unsuitable for a machine learning publication. I can't really speak for the academic philosophy side because I don't know the publication conventions there.
If you want to take this further, your first steps should be to identify the conversation you want to be a part of, and get to know the current landscape of that conversation (I'm mixing metaphors, but you know what I mean).
The conversation is probably mostly a part of the field of Positive Psychology and Meaning in Work literature, a summary of which I cite (Martela and Steger); however, when researching the field (I probably read about 50 academic articles), I didn't see any discussion about value theory (in the realm of philosophy). I have a connection to one of the researchers and maybe I can reach out to start the conversation.
The biggest problem with this paper, as a published scientist, is that I read the abstract and had no idea what your paper was about. Your abstract needs to be more substantial, and cover a) the problem you're addressing, b) the approach you took, and c) the degree to which you succeeded.
Comments from a machine learning / AI focused PhD student. Sorry if I get a bit ridiculous below, I'm up to my neck in coffee and having one of my more "esoteric" days...
0) Golden rules:
- Readability & formatting matters.
- Know your audience.
- Context matters.
- Brevity is best.
- Be clear & concise.
- Abstract, General Intro, Aims, Background/Previous work, Method, Results, Conclusions, Future work => In that order.
- Most important: Nothing goes into the main body unless it makes a tangible, useful & clear contribution.
Some of the best papers are the shortest ones: I can read, understand and explain it to someone else in 1 hour. Among the worst are the 25 pagers that take me 2 days to realise that they aren't useful to me.
1) Footnotes
You aren't commenting code. If it doesn't go in the main text, why is it even there? It is distracting away from the important part - the main body of text.
It either lives in the main text body, a reference or the appendix. If it doesn't live there, then maybe footnote (e.g. a url to some very specific data you trained against).
Get very delete happy with them. For example:
- viii & xiii @ on page 3, xvi @ page 4 should either be in main body (if important, they don't look it), or deleted.
- Things like python commands should just get dumped in the appendix. No footnote / reference. A blanket "you can see all the commands used along with descriptions in the appendix". I'm going to look at what is in the appendix anyway. Because I'm a pedantic academic.
2) Formatting:
- Think about using a template like [1].
- Reduce your font size to 10pt please.
- If you are going to be very maths heavy, think about moving to a single column style. I, personally, find it makes it easier to read eqns and to follow their logic. Currently I have to jump from around the page and keep getting lost.
- For sections 5 & 6: Stop putting something in bold every paragraph. Bold is only tohighlight when it's really important. The name of something is not really important. Prefer italics over bold, but even use that sparingly. How difficult was it to focus on reading this paragraph when the words keep changing shape?
3) Graphs & Tables
Graphs & Tables exist at the top of a page. That's the only place they live if they live in the main body. They don't have to be on the same page as where you refer to them, and you can group them together. Otherwise, appendix that stuff.
Else you'll to end up with blank space (like end of page 4 & 5) and formatting headaches later on.
You haven't done your results discussion part yet... When you do, make sure you don't talk about every single table/graph. Only talk about the results that are important. Otherwise it's guff that will bore your audience.
4) Structure:
You have so many sections that I need a table of contents to work out where I am. For a 10-15 pager, that's silly. Learn to love subsections. Especially those early parts.
5) Intro & Background work:
I have no idea what previous work this relates to. Is there previous work in the field? If so, talk about it. Talk about how you're improving it. Talk about what the context of this paper is.
Don't know what the context is? Then you better find out... People will ask!
6) Quotations
This seems like a technical paper, not an English lit assignment. If you directly quote anything, let alone a whole paragraph, it better blow my mind. I am afraid page 3, column 2 does not. Remove it. Just reference anything like that. If people want/need to know, they will read it too.
I tried to let the figures and tables float but I disliked the strange spacing that resulted. I also tried putting them at the top and it was very hard to follow.
Sorry for the delay; a few unexpected things came up. Thanks again for the thoughtful comments.
> Most important: Nothing goes into the main body unless it makes a tangible, useful & clear contribution.
> Some of the best papers are the shortest ones: I can read, understand and explain it to someone else in 1 hour. Among the worst are the 25 pagers that take me 2 days to realise that they aren't useful to me.
This is an interesting point because I see both sides of it. Brevity can lead to opacity in some cases; however, I agree brevity's a good ideal (in whatever sense brevity is reasonable).
> - viii & xiii @ on page 3, xvi @ page 4 should either be in main body (if important, they don't look it), or deleted.
Agreed, I'll move those to the main body.
> Things like python commands should just get dumped in the appendix. No footnote / reference. A blanket "you can see all the commands used along with descriptions in the appendix". I'm going to look at what is in the appendix anyway. Because I'm a pedantic academic.
Agreed, I'll move the commands to the appendix.
> - Think about using a template like [1].
> - Reduce your font size to 10pt please.
> - If you are going to be very maths heavy, think about moving to a single column style. I, personally, find it makes it easier to read eqns and to follow their logic. Currently I have to jump from around the page and keep getting lost.
I do like the double columns but I'll think about this.
> - For sections 5 & 6: Stop putting something in bold every paragraph. Bold is only to highlight when it's really important. The name of something is not really important. Prefer italics over bold, but even use that sparingly. How difficult was it to focus on reading this paragraph when the words keep changing shape?
I didn't think about that. I'm not sure why I decided to do that, but I agree and I'll remove those.
> Graphs & Tables exist at the top of a page. That's the only place they live if they live in the main body. They don't have to be on the same page as where you refer to them, and you can group them together. Otherwise, appendix that stuff.
> Else you'll to end up with blank space (like end of page 4 & 5) and formatting headaches later on.
Yeah, I had to use `\raggedbottom` for a nice flow. I'll try the more classic way.
> You haven't done your results discussion part yet... When you do, make sure you don't talk about every single table/graph. Only talk about the results that are important. Otherwise it's guff that will bore your audience.
Makes sense.
> You have so many sections that I need a table of contents to work out where I am. For a 10-15 pager, that's silly. Learn to love subsections. Especially those early parts.
I hadn't considered sub-sections. I'll try those out.
> I have no idea what previous work this relates to. Is there previous work in the field? If so, talk about it. Talk about how you're improving it. Talk about what the context of this paper is.
> Don't know what the context is? Then you better find out... People will ask!
As far as I could tell, not much, or very orthogonal, but I've seen this feedback multiple times, so I'll do my best.
> This seems like a technical paper, not an English lit assignment. If you directly quote anything, let alone a whole paragraph, it better blow my mind. I am afraid page 3, column 2 does not. Remove it. Just reference anything like that. If people want/need to know, they will read it too.
That makes sense and I'll remove that huge paragraph. I think it's worthy of highlighting, but best for the appendix. I do wish academic writers would more often quote what they found most relevant from critical papers instead of just using obscure citations.
I'll be away for a few days, but I'll integrate this feedback soon. Thank you very much, again. I'll post an updated draft here when finished, or feel free to email me (see my bio) if you'd rather get a push then pull (and I totally understand if I never hear from you again). If you ever need help with anything, please let me know.
An academic paper is a kind of conversation between experts. You need to describe the problem you're exploring, state what others have done in the area, and finally explain how you are contributing to the problem and show that your contribution is novel.
What you're writing about reads like a combination of philosophy and machine learning. The philosophy probably makes it unsuitable for a machine learning publication. I can't really speak for the academic philosophy side because I don't know the publication conventions there.
If you want to take this further, your first steps should be to identify the conversation you want to be a part of, and get to know the current landscape of that conversation (I'm mixing metaphors, but you know what I mean).