All posts in category Personal Productivity

What to show in your tech resume?

Jason Brinkley on LinkedIn the other day had a comment on the common look of resumes – I disagree with his point in part but it is worth a blog post to say why:

So first, when giving advice I try to be clear about what I think are just my idiosyncratic positions vs advice that I feel is likely to generalize. So when I say, you should apply to many positions, because your probability of landing a single position is small, that is quite general advice. But here, I have personal opinions about what I want to see in a resume, but I do not really know what others want to see. Resumes, when cold applying, probably have to go through at least two layers (HR/recruiter and the hiring manager), who each will need different things.

People who have different colored resumes, or in different formats (sometimes have a sidebar) I do not remember at all. I only care about the content. So what do I want to see in your resume? (I am interviewing for mostly data scientist positions.) I want to see some type of external verification you actually know how to code. Talk is cheap, it is easy to list “I know these 20 python libraries” or “I saved our company 1 million buckaroos”.

So things I personally like seeing in a resume are:

  • code on github that is not a homework assignment (it is OK if unfinished)
  • technical blog posts
  • your thesis! (or other papers you were first/solo author)

Very few people have these things, so if you do and you land in my stack, you are already at the like 95th percentile (if not higher) for resumes I review for jobs.

The reason having outside verification you actually know what you are doing is because people are liars. For our tech round, our first question is “write a python hello world program and execute it from the command line” – around half of the people we interview fail this test. These are all people who list they are experts in machine learning, large language models, years of experience in python, etc.

My resume is excessive, but I try to practice what I preach (HTML version, PDF version)

I added some color, but have had recruiters ask me to take it off the resume before. So how many people actually click all those links when I apply to positions? Probably few if any – but that is personally what I want to see.

There are really only two pieces of advice I have seen repeatedly about resumes that I think are reasonable, but it is advice not a hard rule:

  • I have had recruiters ask for specific libraries/technologies at the top of the resume
  • Many people want to hear about results for project experience, not “I used library X”

So while I dislike the glut of people listing 20 libraries, I understand it from the point of a recruiter – they have no clue, so are just trying to match the tech skills as best they can. (The matching at this stage I feel may be worse than random, in that liars are incentivized, hence my insistence on showing actual skills in some capacity.) It is infuriating when you have a recruiter not understand some idiosyncratic piece of tech is totally exchangeable with what you did, or that it is trivial to learn on the job given your prior experience, but that is not going to go away anytime soon.

I’d note at Gainwell we have no ATS or HR filtering like this (the only filtering is for geographic location and citizenship status). I actually would rather see technical blog posts or personal github code than saying “I saved the company 1 million dollars” in many circumstances, as that is just as likely to be embellished as the technical skills. Less technical hiring managers though it is probably a good idea to translate technical specs to more plain business implications though.

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by apwheele on November 1, 2025  •  Permalink
Posted in data science, Personal Productivity, Python, scholarly
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Posted by apwheele on November 1, 2025

https://andrewpwheeler.com/2025/11/01/what-to-show-in-your-tech-resume/

Deep research and open access

Most of the major LLM chatbot vendors are now offering a tool called deep research. These tools basically just scour the web given a question, and return a report. For academics conducting literature reviews, the parallel is obvious. We just tend to limit the review to peer reviewed research.

I started with testing out Google’s Gemini service. Using that, I noticed almost all of the sources cited were public materials. So I did a little test with a few prompts across the different tools. Below are some examples of those:

  • Google Gemini question on measuring stress in police officers (PDF, I cannot share this chat link it appears)
  • OpenAI Effectiveness of Gunshot detection (PDF, link to chat)
  • Perplexity convenience sample (PDF, Perplexity was one conversation)
  • Perplexity survey measures attitudes towards police (PDF, see chat link above)

The report on officer mental health measures was an area I was wholly unfamiliar. The other tests are areas where I am quite familiar, so I could evaluate how well I thought each tool did. OpenAI’s tool is the most irksome to work with, citations work out of the box for Google and Perplexity, but not with ChatGPT. I had to ask it to reformat things several times. Claude’s tool has no test here, as to use its deep research tool you need a paid account.

Offhand each of the tools did a passable job of reviewing the literature and writing reasonable summaries. I could nitpick things in both the Perplexity and the ChatGPT results, but overall they are good tools I would recommend people become familiar with. ChatGPT was more concise and more on-point. Perplexity got the right answer for the convenience sample question (use post-stratification), but also pulled in a large literature on propensity score matching (which is only relevant for X causes Y type questions, not overall distribution of Y). Again this is nit-picking for less than 5 minutes of work.

Overall these will not magically take over writing your literature review, but are useful (the same way that doing simpler searches in google scholar is useful). The issue with hallucinating citations is mostly solved (see the exception for ChatGPT here). You should consult the original sources and treat deep research reports like on-demand Wikipedia pages, but lets not kid ourselves – most people will not be that thorough.

For the Gemini report on officer mental health, I went through quickly and broke down the 77 citations across the publication type or whether the sources were in HTML or PDF. (Likely some errors here, I went by the text for the most part.) For the HTML vs PDF, 59 out of 77 (76%) are HTML web-sources. Here is the breakdown for my ad-hoc categories for types of publications:

  • Peer Review (open) – 39 (50%)
  • Peer review (just abstract) 10 (13% – these are all ResearchGate)
  • Open Reports 23 (30%)
  • Web pages 5 (6%)

For a quick rundown of these. Peer reviewed should be obvious, but sometimes the different tools cite papers that are not open access. In these cases, they are just using the abstract to madlib how Deep Research fills in its report. (I consider ResearchGate articles here as just abstract, they are a mix of really available, but you need to click a link to get to the PDF in those cases. Google is not indexing those PDFs behind a wall, but the abstract.) Open reports I reserve for think tank or other government groups. Web pages I reserve for blogs or private sector white papers.

I’d note as well that even though it does cite many peer review here, many of these are quite low quality (stuff in MDPI, or other what look to me pay to publish locations). Basically none of the citations are in major criminology journals! As I am not as familiar with this area this may be reasonable though, I don’t know if this material is often in different policing journals or Criminal Justice and Behavior and just not being picked up at all, or if that lit in those places just does not exist. I have a feeling it is missing a few of the traditional crim journal sources though (and picks up a few sources in different languages).

The OpenAI report largely hallucinated references in the final report it built (something that Gemini and Perplexity currently do not do). The references it made up were often portmanteaus of different papers. Of the 12 references it provided, 3 were supposedly peer reviewed articles. You can in the ChatGPT chat go and see the actual web-sources it used (actual links, not hallucinated). Of the 32 web links, here is the breakdown:

  • Pubmed 9
  • The Trace 5
  • Kansas City local news station website 4
  • Eric Piza’s wordpress website 3
  • Govtech website 3
  • NIJ 2

There are single links then to two different journals, and one to the Police Chief magazine. I’d note Eric’s site is not that old (first RSS feed started in February 2023), so Eric making a website where he simple shares his peer reviewed work greatly increased his exposure. His webpage in ChatGPT is more influential than NIJ and peer reviewed CJ journals combined.

I did not do the work to go through the Perplexity citations. But in large part they appear to me quite similar to Gemini on their face. They do cite pure PDF documents more often than I expected, but still we are talking about 24% in the Gemini example are PDFs.

The long story short advice here is that you should post your preprints or postprints publicly, preferably in HTML format. For criminologists, you should do this currently on CrimRXiv. In addition to this, just make a free webpage and post overviews of your work.

These tests were just simple prompts as well. I bet you could steer the tool to give better sources with some additional prompting, like “look at this specific journal”. (Design idea if anyone from Perplexity is listening, allow someone to be able to whitelist sources to specific domains.)

Other random pro-tip for using Gemini chats. They do not print well, and if they have quite a bit of markdown and/or mathematics, they do not convert to a google document very well. What I did in those circumstances was to do a bit of javascript hacking. So go into your dev console (in Chrome right click on the page and select “Inspect”, then in the new page that opens up go to the “Console” tab). And depending on the chat browser currently opened, can try entering this javascript:

// Example printing out Google Gemini Chat
var res = document.getElementsByTagName("extended-response-panel")[0];
var report = res.getElementsByTagName("message-content")[0];
var body = document.getElementsByTagName("body")[0];
let escapeHTMLPolicy = trustedTypes.createPolicy("escapeHTML", {
 createHTML: (string) => string
});
body.innerHTML = escapeHTMLPolicy.createHTML(report.innerHTML);
// Now you can go back to page, cannot scroll but
// Ctrl+P prints out nicely

Or this works for me when revisiting the page:

var report = document.getElementById("extended-response-message-content");
var body = document.getElementsByTagName("body")[0];
let escapeHTMLPolicy = trustedTypes.createPolicy("escapeHTML", {
 createHTML: (string) => string
});
body.innerHTML = escapeHTMLPolicy.createHTML(report.innerHTML);

This page scrolling does not work, but Ctrl + P to print the page does.

The idea behind this, I want to just get the report content, which ends up being hidden away in a mess of div tags, promoted out to the body of the page. This will likely break in the near future as well, but you just need to figure out the correct way to get the report content.

Here is an example of using Gemini’s Deep Research to help me make a practice study guide for my sons calculus course as an example.

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by apwheele on August 28, 2025  •  Permalink
Posted in Criminal Justice, Papers, Personal Productivity, scholarly
Tagged ,

Posted by apwheele on August 28, 2025

https://andrewpwheeler.com/2025/08/28/deep-research-and-open-access/

Some notes on project management

Have recently participated in several projects that I think went well at the day gig – these were big projects, multiple parties, and we came together and got to deployment on a shortened timeline. I think it is worth putting together my notes on why I think this went well.

My personal guiding star for project management is very simple – have a list of things to do, and try to do them as fast as reasonably possible. This is important, as anything that distracts from this ultimate goal is not good. Does not matter if it is agile ceremonies or waterfall excessive requirement gathering. In practice if you are too focused on the bureaucracy either of them can get in the way of the core goals – have a list of things to do and do them in a reasonable amount of time.

For a specific example, we used to have bi-weekly sprints for my team. We stopped doing them for these projects that have IMO gone well, as another group took over project management for the multiple groups. The PM just had an excel spreadsheet, with dates. I did not realize how much waste we had by forcing everything to a two week cycle. We spent too much time trying to plan two weeks out, and ultimately not filling up peoples plates. It is just so much easier to say “ok we want to do this in two days, and then this in the next three days” etc. And when shit happens just be like “ok we need to push X task by a week, as it is much harder than anticipated”, or “I finished Y earlier, but I think we should add a task Z we did not anticipate”.

If sprints make sense for your team go at it – they just did not for my team. They caused friction in a way that was totally unnecessary. Just have a list of things to do, and do them as fast as reasonably possible.

Everything Parallel

So this has avoided the hard part, what to put on the to-do list? Let me discuss another very important high level goal of project management first – you need to do everything in parallel as much as possible.

For a concrete example that continually comes up in my workplace, you have software engineering (writing code) vs software deployment (how that code gets distributed to the right people). I cannot speak to other places (places with a mono-repo/SaaS it probably looks different), but Gainwell is really like 20+ companies all Frankenstein-ed together through acquisitions and separate big state projects over time (and my data science group is pretty much solution architects for AI/ML projects across the org).

It is more work for everyone in this scenario trying to do both writing code and deployment at the same time. Software devs have to make up some reasonably scoped requirements (which will later change) for the DevOps folks to even get started. The DevOps folks may need to work on Docker images (which will later change). So it is more work to do it in parallel than it is sequential, but drastically reduces the overall deliverable timelines. So e.g. instead of 4 weeks + 4 weeks = 8 weeks to deliver, it is 6 weeks of combined effort.

This may seem like “duh Andy” – but I see it all the time people not planning out far enough though to think this through (which tends to look more like waterfall than agile). If you want to do things in months and not quarters, you need everyone working on things in parallel.

For another example at work, we had a product person want to do extensive requirements gathering before starting on the work. This again can happen in parallel. We have an idea, devs can get started on the core of it, and the product folks can work with the end users in the interim. Again more work, things will change, devs may waste 1 or 2 or 4 weeks building something that changes. Does not matter, you should not wait.

I could give examples of purely “write code as well”, e.g. I have one team member write certain parts of the code first, which are inconvenient, because that component not being finished is a blocker for another member of the team. Basically it is almost always worth working harder in the short term if it allows you to do things in parallel with multiple people/teams.

Sometimes the “in parallel” is when team members have slack, have them work on more proof of concept things that you think will be needed down the line. For the stuff I work on this can IMO be enjoyable, e.g. “you have some time, lets put a proof of concept together on using Codex + Agents to do some example work”. (Parallel is not quite the word for this, it is forseeing future needs.) But it is similar in nature, I am having someone work on something that will ultimately change in ways in the future that will result in wasted effort, but that is OK, as the head start on trying to do vague things is well worth it.

What things to put on the list

This is the hardest part – you need someone who understands front to back what the software solution will look like, how it interacts with the world around it (users, databases, input/output, etc.) to be able to translate that vision into a tangible list of things to-do.

I am not even sure if I can articulate how to do this in a general enough manner to even give useful advice. When I don’t know things front to back though I will tell you what, I often make mistakes going down paths that often waste months of work (which I think is sometimes inevitable, no one had the foresight to know it was a bad path until we got quite a ways down it).

I used to think we should do the extensive, months long, requirements gathering to avoid this. I know a few examples where I talked for months with the business owners, came up with a plan, and then later on realized it was based on some fundamental misunderstanding of the business. And the business team did not have enough understanding of the machine learning model to know it did not make sense.

I think mistakes like these are inevitable though, as requirements gathering is a two way street (it is not reasonable for any of the projects I work on to expect the people requesting things to put together a full, scoped out list). So just doing things and iterating is probably just as fast as waiting for a project to be fully scoped out.

Do them as fast as possible

So onto the second part, of “have a list of things to-do and do them as fast as possible”. One of the things with “fast as possible”, people will fill out their time. If you give someone two weeks to do something, most people will not do it faster, they will spend the full two weeks doing that task.

So you need someone technical saying “this should be done in two days”. One mistake I see teams make, is listing out projects that will take several weeks to-do. This is only OK for very senior people. Majority of devs tasks should be 1/2/3 days of work at max. So you need to take a big project and break it down into smaller components. This seems like micro-managing, but I do not know how else to do it and keep things on track. Being more specific is almost always worth my time as opposed to less specific.

Sometimes this even works at higher levels, one of the projects that went well, initial estimates were 6+ months. Our new Senior VP of our group said “nope, needs to be 2-3 months”. And guess what? We did it (he spent money on some external contractors to do some work, but by god we did it). Sometimes do them as fast as possible is a negotiation at the higher levels of the org – well you want something by end of Q3, well we can do A and C, but B will have to wait until later then, and the solution will be temporarily deployed as a desktop app instead of a fully served solution.

Again more work for our devs, but shorter timeline to help others have an even smaller MVP totally makes sense.

AI will not magically save you

Putting this last part in, as I had a few conversations recently about large code conversion projects teams wanted to know if they could just use AI to make short work of it. The answer is yes it makes sense to use AI to help with these tasks, but they expected somewhat of a magic bullet. They each still needed to make a functional CICD framework to test isolated code changes for example. They still needed someone to sit down and say “Joe and Gary and Melinda will work on this project, and have XYZ deliverables in two months”. A legacy system that was built over decades is not a weekend project to just let the machine go brr and churn out a new codebase.

Some of them honestly are groups that just do not want to bite the bullet and do the work. I see projects that are mismanaged (for the criminal justice folks that follow me, on-prem CAD software deployments should not take 12 months). They take that long because the team is mismanaged, mostly people saying “I will do this high level thing in 3 months when I get time”, instead of being like “I will do part A in the next two days and part B in the three days following that”. Or doing things sequentially that should be done in parallel.

To date, genAI has only impacted the software engineering practices of my team at the margins (potentially writing code slightly faster, but probably not). We are currently using genAI in various products though for different end users. (We have deployed many supervised learning models going back years, just more recently have expanded into using genAI for different tasks though in products.)

I do not foresee genAI taking devs jobs in the near future, as there is basically infinite amounts of stuff to work on (everything when you look closely is inefficient in a myriad of ways). Using the genAI tools to write code though looks very much like project management, identifying smaller and more manageable tasks for the machine to work on, then testing those, and moving onto the next steps.

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by apwheele on July 20, 2025  •  Permalink
Posted in data science, Personal Productivity
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Posted by apwheele on July 20, 2025

https://andrewpwheeler.com/2025/07/20/some-notes-on-project-management/

LinkedIn is the best social media site

The end goals I want for a social media site are:

  • promote my work
  • see other peoples work

Social media for other people may have other uses. I do comment and have minor interactions on the social media sites, but I do not use them primarily for that. So my context is more business oriented (I do not have Facebook, and have not considered it). I participate some on Reddit as well, but that is pretty sparingly.

LinkedIn is the best for both relative to X and BlueSky currently. So I encourage folks with my same interests to migrate to LinkedIn.

LinkedIn

So I started Crime De-Coder around 2 years ago. I first created a website, and then second started a LinkedIn page.

When I first created the business page, I invited most of my criminal justice contacts to follow the page. I had maybe 500 followers just based on that first wave of invites. At first I posted once or twice a week, and it was very steady growth, and grew to over 1500 followers in maybe just a month or two.

Now, LinkedIn has a reputation for more spammy lifecoach self promotion (for lack of a better description). I intentionally try to post somewhat technical material, but keep it brief and understandable. It is mostly things I am working on that I think will be of interest to crime analysts or the general academic community. Here is one of my recent posts on structured outputs:

Current follower count on LinkedIn for my business page (which in retrospect may have been a mistake, I think they promote business pages less than personal pages), is 3230, and I have fairly consistent growth of a few new followers per day.

I first started posting once a week, and with additional growth expanded to once every other day and at one point once a day. I have cut back recently (mostly just due to time). I did get more engagement, around 1000+ views per day when I was posting every day.

Probably the most important part though of advertising Crime De-Coder is the types of views I am getting. My followers are not just academic colleagues I was previously friends with, it is a decent outside my first degree network of police officers and other non-profit related folks. I have landed several contracts where I know those individuals reached out to me based on my LinkedIn posting. It could be higher, as my personal Crime De-Coder website ranks very poorly on Bing search, but my LinkedIn posts come up fairly high.

When I was first on Twitter I did have a few academic collaborations that I am not sure would have happened without it (a paper with Manne Gerell, and a paper with Gio Circo, although I had met Gio in real life before that). I do not remember getting any actual consulting work though.

I mentioned it is not only better for me for advertising my work, but also consuming other material. I did a quick experiment, just opened the home page and scrolled the first 3 non-advertisement posts on LinkedIn, X, and BlueSky. For LinkedIn

This is likely a person I do not want anything to do with, but their comment I agree with. Whenever I use Service Now at my day job I want to rage quit (just send a Teams chat or email and be done with it, LLMs can do smarter routing anymore). The next two are people are I am directly connected with. Some snark by Nick Selby (which I can understand the sentiment, albeit disagree with, I will not bother to comment though). And something posted by Mindy Duong I likely would be interested in:

Then another advert, and then a post by Chief Patterson of Raleigh, whom I am not directly connected with, but was liked by Tamara Herold and Jamie Vaske (whom I am connected with).

So annoying for the adverts, but the suggested (which the feeds are weird now, they are not chronological) are not bad. I would prefer if LinkedIn had a “general” and “my friends” sections, but overall I am happier with the content I see on LinkedIn than I am the other sites.

X & BlueSky

I first created a personal then Twitter account in 2018. Nadine Connell suggested it, and it was nice then. When I first joined I think it was Cory Haberman tweeted and said to follow my work, and I had a few hundred followers that first day. Then over the next two years, just posting blog posts and papers for the most part, I grew to over 1500 followers IIRC. I also consumed quite a bit of content from criminal justice colleagues. It was much more academic focused, but it was a very good source of recent research, CJ relevant news and content.

I then eventually deleted the Twitter account, due to a colleague being upset I liked a tweet. To be clear, the colleague was upset but it wasn’t a very big deal, I just did not want to deal with it.

I started a Crime De-Coder X account last year. I made an account to watch the Trump interview, and just decided to roll with it. I tried really hard to make X work – I posted daily, the same stuff I had been sharing on LinkedIn, just shorter form. After 4 months, I have 139 followers (again, when I joined Twitter in 2018 I had more than that on day 1). And some of those followers are porn accounts or bots. Majority of my posts get <=1 like and 0 reposts. It just hasn’t resulted in getting my work out there the same way in 2018 or on LinkedIn now.

So in terms of sharing work, the more recent X has been a bust. In terms of viewing other work, my X feed is dominated by short form video content (a mimic of TikTok) I don’t really care about. This is after extensively blocking/muting/saying I don’t like a lot of content. I promise I tried really hard to make X work.

So when I open up the Twitter home feed, it is two videos by Musk:

Then a thread by Per-Olof (whom I follow), and then another short video Death App joke:

So I thought this was satire, but clicking that fellows posts I think he may actually be involved in promoting that app. I don’t know, but I don’t want any part of it.

BlueSky I have not been on as long, but given how easy it was to get started on Twitter and X, I am not going to worry about posting so much. I have 43 followers, and posts similar to X have basically been zero interaction for the most part. The content feed is different than X, but is still not something I care that much about.

We have Jeff Asher and his football takes:

I am connected with Jeff on LinkedIn, in which he only posts his technical material. So if you want to hear Jeff’s takes on football and UT-Austin stuff then go ahead and follow him on BlueSky. Then we have a promotional post by a psychologist (this person I likely would be interested in following his work, this particular post though is not very interesting). And a not funny Onion like post?

Then Gavin Hales, whom I follow, and typically shares good content. And another post I leave with no comment.

My BlueSky feed is mostly dominated by folks in the UK currently. It could be good, but it currently just does not have the uptake to make it worth it like I had with Twitter in 2018. It may be the case given my different goals, to advertise my consulting business, Twitter in 2018 would not be good either though.

So for folks who subscribe to this blog, I highly suggest to give LinkedIn a try for your social media consumption and sharing.

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by apwheele on February 20, 2025  •  Permalink
Posted in data science, Personal Productivity, scholarly, social networking, writing
Tagged ,

Posted by apwheele on February 20, 2025

https://andrewpwheeler.com/2025/02/20/linkedin-is-the-best-social-media-site/

Year in Review 2024

Past year in review posts I have made focused on showing blog stats. Writing this in early December, but total views will likely be down this year – I am projecting around 140,000 views in total for this site. But I have over 25k views for the Crime De-Coder site, so it is pretty much the same compared to 2023 combining the two sites.

I do not have a succinct elevator speech to tell people what I am working on. With the Crime De-Coder consulting gig, it can be quite eclectic. That Tukey quote being a statistician you get to play in everyone’s backyard is true. Here is a rundown of the paid work I conducted in the past year.

Evidence Based CompStat: Work with Renee Mitchell and the American Society of Evidence Based Policing on what I call Evidence Based CompStat. This mostly amounts to working directly with police departments (it is more project management than crime analysis) to help them get started with implementing evidence based practices. Reach out if that sounds like something your department would be interested in!

Estimating DV Violence: Work supported by the Council on CJ. I forget exactly the timing of events. This was an idea I had for a different topic (to figure out why stores and official reports of thefts were so misaligned). Alex approached me to help with measuring national level domestic violence trends, and I pitched this idea (use local NIBRS data and NCVS to get better local estimates).

Premises Liability: I don’t typically talk about ongoing cases, but you can see a rundown of some of the work I have done in the past. It is mostly using the same stats I used as a crime analyst, but in reference to civil litigation cases.

Patrol Workload Analysis: I would break workload analysis for PDs down into two categories, advanced stats and CALEA reports. I had one PD interested in the simpler CALEA reporting requirement (which I can do for quite a bit cheaper than the other main consulting firm that offers these services).

Kansas City Python Training: Went out to Kansas City for a few days to train their analysts up in using python for Focused Deterrence. If you think the agenda in the pic below looks cool get in touch, I would love to do more of these sessions with PDs. I make it custom for the PD based on your needs, so if you want “python and ArcGIS”, or “predictive models” or whatever, I will modify the material to go over those advanced applications. I have also been pitching the same idea (short courses) for PhD programs. (So many posers in private sector data science, I want more social science PhDs with stronger tech skills!)

Patterson Opioid Outreach: Statistical consulting with Eric Piza and Kevin Wolff on a street outreach intervention intended to reduce opioid overdose in Patterson New Jersey. I don’t have a paper to share for that at the moment, but I used some of the same synthetic control in python code I developed.

Bookstore prices: Work with Scott Jacques, supported by some internal GSU money. Involves scraping course and bookstore data to identify the courses that students spend the most on textbooks. Ultimate goal in mind is to either purchase those books as unlimited epubs (to save the students money), or encourage professors to adopt better open source materials. It is a crazy amount of money students pour into textbooks. Several courses at GSU students cumulatively spend over $100k on course materials per semester. (And since GSU has a large proportion of Pell grant recipients, it means the federal government subsidizes over half of that cost.)

General Statistical Consulting: I do smaller stat consulting contracts on occasion as well. I have an ongoing contract to help with Pam Metzger’s group at the SMU Deason center. Did some small work for AH Datalytics on behind the scenes algorithms to identify anomalous reporting for the real time crime index. I have several times in my career consulted on totally different domains as well, this year had a contract on calculating regression spline curves for some external brain measures.

Data Science Book: And last (that I remember), I published Data Science for Crime Analysis with Python. I still have not gotten my 100 sales I would consider it a success – so if you have not bought a copy go do that right now. (Coupon code APWBLOG will get you $10 off for the next few weeks, either the epub or the paperback.)

Sometimes this seems like I am more successful than I am. I have stopped counting the smaller cold pitches I make (I should be more aggressive with folks, but most of this work is people reaching out to me). But in terms of larger grant proposals or RFPs in that past year, I have submitted quite a few (7 in total) and have landed none of them to date! Submitted a big one to support surveys that myself and Gio won the NIJ competition on for place based surveys to NIJ in their follow up survey solicitation, and it was turned down for example. So it goes.

In addition to the paid work, I still on occasion publish peer reviewed articles. (I need to be careful with my time though.) I published a paper with Kim Rossmo on measuring the buffer zone in journey to crime data. I also published the work on measuring domestic violence supported by the Council on CJ with Alex Piquero.

I took the day gig in Data Science at the end of 2019. Citations are often used as a measure of a scholars influence on the field – they are crazy slow though.

I had 208 citations by the end of 2019, I now have over 1300. Of the 1100 post academia, only a very small number are from articles I wrote after I left (less than 40 total citations). A handful for the NIJ recidivism competition paper (with Gio), and a few for this Covid and shootings paper in Buffalo. The rest of the papers that have a post 2019 publishing date were entirely written before I left academia.

Always happy to chat with folks on teaming up on papers, but it is hard to take the time to work on a paper for free if I have other paid work at the moment. One of the things I need to do to grow the business is to get some more regular work. So if you have a group (academic, think tank, public sector) that is interested in part time (or fractional I guess is what the cool kids are calling it these days), I would love to chat and see if I could help your group out.

Leave a comment
by apwheele on December 3, 2024  •  Permalink
Posted in Crime Analysis, Criminal Justice, data science, Personal Productivity, website, writing
Tagged ,

Posted by apwheele on December 3, 2024

https://andrewpwheeler.com/2024/12/03/year-in-review-2024/

LinkedIn posting and link promotion: impression vs reality

For folks who are interested in following my work, my advice is either email or RSS. This site you should see ‘follow blog via email’ and the RSS link on the right hand side. I sometimes post a note here on crimede-coder stuff, but not always, so just do the same (RSS, or use if-this-than-that service to turn RSS into email) on that site if you want to keep abreast of all my posts.

Another way to follow my work though is on LinkedIn. So feel free to connect with me or follow my content:

I post short form blogs/reactions on occasion (plus share my other posts/work). Social media promoting your work is often cringy, but I try to post informative and technical content (and not totally vapid self-help stuff). And I write things for people to view them, so I think it is important to promote my work.

One of the most recent things I have heard a few influencers mention how embedding links directly in LinkedIn posts they think de-promotes their work. See this discussion on HackerNews, or this person’s advice for two examples.

I formed a few opinions based on my regular postings over the past year+, but impressions of things over extended periods can often be wrong. So I actually downloaded the data to see! In terms of the thing about links and being de-promoted, I don’t see that in my data at all – this is a table of impressions broken down by the domain I linked to (for domains with at least 2+ posts over the prior year):

I did notice however two different domains – youtube and newsobserver (the Raleigh newspaper) tend to not have much engagement. So it may be certain domains are not as promoted. It is of course possible that particular content was not popular (I thought my crim observations on the Mark Rober glitterbombs would be more popular, but maybe not). But I think this is a large enough sample to at least give a good hint that they are not promoted in the same way my other links are. My no URL posts have slightly less engagement than my posts to this blog or the crimede-coder site, so overall the idea that links are penalized doesn’t appear to me to be true without more conditional statements.

Data is important, as again I think impressions can be bad for things that repeatedly happen over a long period of time. So offhand I though Tue/Thu I had less engagement, so stopped posting on those days. What does the data say?

| Day | Avg Impressions | Number Posts |
----------------------------------------
| Sun |         1,860   |         32   |
| Mon |         1,370   |         44   |
| Tue |         1,220   |         35   |
| Wed |         1,273   |         41   |
| Thu |         1,170   |         34   |
| Fri |         1,039   |         39   |
| Sat |         1,602   |         38   |

The data says Sun/Sat have higher impressions, and days of the week are lower. If anything Friday is the low day, not Tuesday/Thursday.

I have had other examples of practitioners argue with me in crime analysis or academic circles in my career that strike me as similar. In that perceptions (that people strongly believed in), did not align with actual data. So I just don’t think this idea of ‘taking the average of impressions over posts over the past year’ is something that you can really know just based on passive observation. Your perceptions are likely to be dominated by a few examples, which may be off the mark. Ditto for knowing how much crime happens at a particular location, or knowing how much different things impact survival rates for gunshots.

It is definately possible that my small page experience (currently at a few over 2700 followers on LinkedIn) is not the same as the large influencers. But without looking at actual data, I don’t trust peoples instincts on aggregate metrics all that much.

Another meta LinkedIn tip (I received from Rob Fornango) is to post tall images, so when people are scrolling your content stays on the screen longer. Here is an example post from Rob’s

It is hard for me to test this though, the links on LinkedIn sometimes expand the link to bigger images and sometimes not (and sometimes I edit the image it displays as well). And I think after a while they turn them into tiny images as well. Someone tell the folks on LinkedIn to allow us to use markdown!

So I mean I could spend a full time job tinkering, but looking at the data I have at hand I don’t plan on changing much. Just posting links to my work, and having an occasional comment as well if I think it will be of interest to more people than myself. Content over micro optimization that is (since the algorithm could change tomorrow anyway).

One of the things I have debated on is buying adverts to promote my python book. I think they are just on the cusp of a net loss though given clickthrough rates and margins on my book. So for example, LinkedIn estimates if I spend $140 to promote a post, I will get 23-99 clicks. My buy rate on the site is around 5%, so that would generate 1-5 book sales. My margins are not that high on a sale, so I would not make money on that.

I have been wondering if I posted direct adverts on Reddit for the book to the learn python forum how that would go. But I think it would be much of the same as LinkedIn (too low of clickthrough to make it worth it). But if I do those tests in the future will write up a blog post on my experience!

LinkedIn I can only find how to download my stats on the company crimede-coder page, not my personal page. Here is the script I used to convert the LinkedIn short urls back to the original domains I linked, plus the analysis:

'''
python Code to parse the domains from my
crimede-coder linkedin posts
run on 7/24/2024, so only has posts
from that date through the prior year
'''

import requests
import traceback
import pandas as pd
import time
from urllib.parse import urlparse

errors = {}

def get_link(url):
    time.sleep(2)
    try:
        res = requests.get(url)
    except Exception:
        er = traceback.format_exc()
        print(f'Error message is \n\n{er}')
        return ''
    if res.ok:
        it = res.text.split()
        it = [i for i in it if i[:4] == 'href']
        rl = it[3]
    else:
        print(f'Not ok, {url}, response: {r2.reason}')
        errors[url] = res
        return ''
    return rl[6:].replace('/">','').replace('">','')

# more often than not, linkedin converts the link in the post
# to a lnkd.in short url
def get_refer(txt):
    rs = txt.split()
    rs = [i for i in rs if i[:8] == 'https://']
    if rs:
        url = rs[0]  # if more than one link, only grabs the first
        if url[:15] == 'https://lnkd.in':
            return get_link(url)
        else:
            return url
    else:
        return ''


# this is data exported from LinkedIn on my Crime De-Coder page only goes back one year
df = pd.read_excel('crime-de-coder_content_1721834275879.xls',sheet_name='All posts',header=1)

# only need to keep a few columns
keep_cols = ['Post title','Post link','Created date','Impressions','Clicks','Likes','Comments','Reposts']
df = df[keep_cols].copy()

df['url'] = df['Post title'].apply(get_refer)

def domain(url):
    if url == '':
        return 'NO URL'
    else:
        pu = urlparse(url)
        return pu.netloc

df['domain'] = df['url'].apply(domain)

# caching out file, so do not need to reget url info
df.to_csv('ParseInfo.csv',index=False)

# Can aggregate to domain
agg_stats = df.groupby('domain',as_index=False)['Impressions'].describe()
agg_stats.sort_values(by=['count','mean'],ascending=False,ignore_index=True,inplace=True)
count_cols = list(agg_stats)[1:]
agg_stats[count_cols] = agg_stats[count_cols].fillna(0).astype(int)

# This is a nice way to print/view the results in terminal
print('\n\n' + agg_stats.head(22).to_markdown() + '\n\n')
1 Comment
by apwheele on July 25, 2024  •  Permalink
Posted in Personal Productivity, social networking, website, writing
Tagged ,

Posted by apwheele on July 25, 2024

https://andrewpwheeler.com/2024/07/25/linkedin-posting-and-link-promotion-impression-vs-reality/

Some notes on self-publishing a tech book

So my book, Data Science for Crime Analysis with Python, is finally out for purchase on my Crime De-Coder website. Folks anywhere in the world can purchase a paperback or epub copy of the book. You can see this post on Crime De-Coder for a preview of the first two chapters, but I wanted to share some of my notes on self publishing. It was some work, but in retrospect it was worth it. Prior books I have been involved with (Wheeler 2017; Wheeler et al. 2021) plus my peer review experience I knew I did not need help copy-editing, so the notes are mostly about creating the physical book and logistics of selling it.

Academics may wish to go with a publisher for prestige reasons (I get it, I was once a professor as well). But it is quite nice once you have done the legwork to publish it yourself. You have control of pricing, and if you want to make money you can, or have it cheap/free for students.

Here I will detail some of the set up of compiling the book, and then the bit of work to distribute it.

Compiling the documents

So the way I compiled the book is via Quarto. I posted my config notes on how to get the book contents to look how I wanted on GitHub. Quarto is meant to run code at the same time (so works nicely for a learning to code book). But even if I just wanted a more typical science/tech book with text/images/equations, I would personally use Quarto since I am familiar with the set up at this point. (If you do not need to run dynamic code you could do it in Pandoc directly, not sure if there is a way to translate a Quarto yaml config to the equivalent Pandoc code it turns into.)

One thing that I think will interest many individuals – you write in plain text markdown. So my writing looks like:

# Chapter Heading

blah, blah blah

## Subheading

Cool stuff here ....

In a series of text files for each chapter of the book. And then I tell Quarto quarter render, and it turns my writing in those text files into both an Epub and a PDF (and other formats if you cared, such as word or html). You can set up the configuration for the book to be different for the different formats (for example I use different fonts in the PDF vs the epub, nice fonts in one look quite bad in the other). See the _quarto.yml file for the set up, in particular config options that are different for both PDF and Epub.

One thing is that ebooks are hard to format nicely – if I had a book I wanted to redo to be an epub, I would translate it to markdown. There are services online that will translate, they will do a bad job though with scientific texts with many figures (and surely will not help you choose nice fonts). So just learn markdown to translate. Folks who write in one format and save to the other (either Epub/HTML to PDF, or PDF to Epub/HTML) are doing it wrong and the translated format will look very bad. Most advice online is for people who have just books with just text, so science people with figures (and footnotes, citations, hyperlinks, equations, etc.) it is almost all bad advice.

So even for qualitative people, learning how to write in markdown to self-publish is a good skill to learn in my opinion.

Setting up the online store

For awhile I have been confused how SaaS companies offer payment plans. (Many websites just seem to copy from generic node templates.) Looking at the Stripe API it just seems over the top for me to script up all of my own solution to integrate Stripe directly. If I wanted to do a subscription I may need to figure that out, but it ended up being for my Hostinger website I can set up a sub-page that is WordPress (even though the entire website is not), and turn on WooCommerce for that sub-page.

WooCommerce ends up being easy, and you can set up the store to host web-assets to download on demand (so when you purchase it generates a unique URL that obfuscates where the digital asset is saved). No programming involved to set up my webstore, it was all just point and click to set things up one time and not that much work in the end.

I am not sure about setting up any DRM for the epub (so in reality people will purchase epub and share it illegally). I don’t know of a way to prevent this without using Amazon+Kindle to distribute the book. But the print book should be OK. (If there were a way for me to donate a single epub copy to all libraries in the US I would totally do that.)

I originally planned on having it on Amazon, but the low margins on both plus the formatting of their idiosyncratic kindle book format (as far as I can tell, I cannot really choose my fonts) made me decide against doing either the print or ebook on Amazon.

Print on Demand using LuLu

For print on demand, I use LuLu.com. They have a nice feature to integrate with WooCommerce, the only thing I wish shipping was dynamically calculated. (I need to make a flat shipping rate for different areas around the globe the way it is set up now, slightly annoying and will change the profit margins depending on area.)

LuLu is a few more dollars to print than Amazon, but it is worth it for my circumstance I believe. Now if I had a book I expected to get many “random Amazon search buys” I could see wanting it on Amazon. I expect more sales will be via personal advertising (like here on the blog, social media, or other crime analyst events). My Crime De-Coder site (and this blog) will likely be quite high in google searches for some of the keywords fairly quickly, so who knows, maybe just having on personal site is just as many sales.

LuLu does has an option to turn on distribution to other wholesalers (like Barnes & Noble and Amazon) – have not turned that on but maybe I will in the future.

LuLu has a pricing calculator to see how much to print on their website. Paperback and basically the cheapest color option for letter sized paper (which is quite large) is just over $17 for my 310 page book (Amazon was just over $15). For folks if you are less image heavy and more text, you could get away with a smaller size book (and maybe black/white) and I suspect will be much cheaper. LuLu’s printing of this book is higher quality compared to Amazon as well (better printing of the colors and nicer stock for the paperback cover).

Another nice thing about print on demand is I can go in and edit/update the book as I see fit. No need to worry about new versions. Not sure what that exactly means for citing the work (I could always go and change it), you can’t have a static version of record and an easy way to update at the same time.

Other Random Book Stuff

I purchased ISBNs on Bowker, something like 10 ISBNs for $200. (You want a unique ISBN for each type of the book, so you may want three in the end if you have epub/paperback/hardback.) Amazon and LuLu though have options to have them give you an ISBN though, so that may have not been necessary. I set the imprint to be my LLC though in Bowker, so CRIME De-Coder is the publisher.

You don’t technically need an ISBN at all, but it is a simple thing, and there may be ways for me to donate to libraries in the future. (If a University picks it up as a class text, I have been at places you need at least one copy for rent at the Uni library.)

I have not created an index – I may have a go at feeding my book through LLMs and seeing if I can auto-generate a nice index. (I just need a list of key words, after that can just go and find-replace the relevent text in the book to fill in so it auto-compiles an index.) I am not sure that is really necessary though for a how-to book, you should just look at the table of contents to see the individual (fairly small) sections. For epub you can just doing a direct text search, so not sure if people use an index at all in epubs.

Personal Goals

So I debated on releasing the book open source, I do want to try and see if I can make some money though. I don’t have this expectation, but there is potential to get some “data science” spillover, and if that is the case sales could in theory be quite high. (I was surprised in searching the “data science python” market on Amazon, it is definitely not saturated.) Personally I will consider at least 100 sales to be my floor for success. That is if I can sell at least 100 copies, I will consider writing more books. If I can’t sell 100 copies I have a hard time justifying the effort – it would just be too few of people buying the book to have the types of positive spillovers I want.

To make back money relative to the amount of work I put in, I would need more than 1000 sales (which I think is unrealistic). I think 500 sales is about best case, guesstimating the size of the crime analyst community that may be interested plus some additional sales for grad students. 1000 sales it would need to be in the multiple professors using it for a class book over several years. (Which if you are a professor and interested in this for a class let me know, I will give your class a discount.)

Another common way for individuals to make money off of books is not for sales, but to have training’s oriented around the book. I am hoping to do more of that for crime analysts directly in the future, but those opportunities I presume will be correlated with total sales.

I do enjoy writing, but I am busy, so cannot just say “I am going to drop 200 hours writing a book”. I would like to write additional python topics oriented towards crime analysts/criminology grad students like:

  • GIS analysis in python
  • Regression
  • Machine Learning & Optimization
  • Statistics for Crime Analysis
  • More advanced project management in python

Having figured out much of this grunt work definitely makes me more motivated, but ultimately in the end need to have a certain level of sales to justify the effort. So please if you like the blog pick up a copy and tell a friend you like my work!

References

5 Comments
by apwheele on July 2, 2024  •  Permalink
Posted in Crime Analysis, Criminal Justice, data science, Personal Productivity, Python, writing
Tagged ,

Posted by apwheele on July 2, 2024

https://andrewpwheeler.com/2024/07/02/some-notes-on-self-publishing-a-tech-book/

Ask me anything: Advice for learning statistics?

For a bit of background, Loki, a computer science student in India, was asking me about my solution to the DrivenData algae bloom competition. Much of our back and forth was specific to my coding solution and “how I knew how to do that” (in particular I used a machine learning variant of doubly robust estimation in part of the solution, which I am sure others have used before but is not real common that I see, it is more often “causal inference” motivated). As for more general advice in learning, I said:

Only advice is to learn stats – not just for competitions but for real-world jobs. Many people are just copy-pasting code, and don’t know what they are doing. Understanding selection bias is important in many real-world scenarios. Often times it is just knowing a little about the scientific scenario you are modeling, and correctly formulating a model.

In response Loki asks:

I decided to take your suggestion and strengthen my grasp on statistics. I consider myself somewhere between beginner to intermediate in stats. I came across several resources on the internet, but feel confused about what to go with. I am wondering if “The Elements of Statistical Learning” by Trevor Hastie and Robert Tibishirani is a good one to start with. Or could you please suggest any books/lectures/courses that have practical applications to solidify my understanding of statistics that you have personally read or liked?

Which I think is a good piece to expand to the readers on my blog in general. Here is my response:

I would not start with that book. It is a mistake to start with too advanced of material. (I don’t learn anything that way anyway.)

Starting from the basics, no joke Gonick’s Cartoon Guide to Statistics is in my opinion the best intro to statistics and probability book. After that, it is important to understand causality – like really understand it – selection bias lurks everywhere. (I am not sure I have great advice for books that focus on causality, Pearl’s book is quite tough, maybe Shadish, Cook, Campbell Experimental and Quasi-Experimental Designs and/or Mostly Harmless Econometrics).

After that, follow questions on https://stats.stackexchange.com, it is high quality on average (many internet sources, like Medium articles or https://datascience.stackexchange.com, are very low quality on average – they can have gems but more often than not they are bad for anything besides copy/pasting code). Andrew Gelman’s blog is another good source for contemporary discussion around stats/research/pitfalls, https://statmodeling.stat.columbia.edu.

In terms of more advanced modeling, after having the basics down, I would suggest Harrell’s Regression Modeling Strategies before the Hastie book. You can interpret pretty much all of machine learning in terms of regression models. For small datasets, understanding how to do simpler regression modeling the right way is the best approach.

When moving onto machine learning, then maybe the Hastie book is a good resource (I didn’t find it all that much useful at this point beyond web resources). Statquest videos are very good walkthroughs of more complicated ML algorithms, https://www.youtube.com/@statquest, trees/boosting/neural-networks.

This is a hodge-podge – I don’t tend to learn things just to learn them – I have a specific project in mind and try to tackle that project the best I can. Many of these resources are items I picked up along the way (Gonick I got to review intro stats books for teaching, Harrell’s I picked up to learn a bit more about non-linear modeling with splines, Statquest I reviewed when interviewing for data science positions).

It is a long road to get to where I am. It was not via picking a book and doing intense study, it was a combination of applied projects and learning new things over time. I learned a crazy lot from the Cross Validated site when I was in grad school. (For those interested in optimization, the Operations Research site is also very high quality.) That was more broad learning though – seeing how people tackled problems in different domains.

1 Comment
by apwheele on March 17, 2023  •  Permalink
Posted in ask me anything, data science, Personal Productivity
Tagged

Posted by apwheele on March 17, 2023

https://andrewpwheeler.com/2023/03/17/ask-me-anything-advice-for-learning-statistics/

Crime De-Coder LLC Website

So I have created CRIME De-Coder LLC, a firm to do my consulting work with police departments. Check out my website, crimede-coder.com.

Feedback is welcome. In particular check out the services pages, and my first blog post on what distinguishes my services from most firms. Providing computer code to generate the end product is “teaching a man a fish”, whereas most firms just drop a final report and leave.

And of course feel free to reach out to consult@crimede-coder.com if you are interested in pursuing a project. Going forward I plan on making a new post around once a month, so sign up in your feed reader or using a service like IFTTT.

Setting up a stand alone website is not that hard in the end. Currently it is a static site with some custom javascript (hosted on Hostinger). I should do a PHP server for the new blog posts and RSS feed eventually, but for now this is fine. I suggest for those interested in the same get the Jon Duckett books (HTML/Javascript/PHP) for overview of the tech, and then check out Dani Kross’s youtube tutorials (for random things like editing the htaccess file).

I am not doing a newsletter for the blog-posts, as I am concerned it will get my email on random block lists. But if there is demand for it in the future I will figure out some other service I guess to do that.

I wanted a more bare-metal setup (not a hosted wordpress like this site), as in the future I will likely do demo’s of dashboards, host some pyscript, make a sign in for paid content, etc. I just wanted flexibility from the start. So stay tuned for more content from CRIME De-Coder!

3 Comments
by apwheele on February 22, 2023  •  Permalink
Posted in Crime Analysis, Crime Mapping, Criminal Justice, data science, Personal Productivity, website
Tagged ,

Posted by apwheele on February 22, 2023

https://andrewpwheeler.com/2023/02/22/crime-de-coder-llc-website/

Getting access to paywalled newspaper and journal articles

So recently several individuals have asked about obtaining articles they do not have access to that I cite in my blog posts. (Here or on the American Society of Evidence Based Policing.) This is perfectly fine, but I want to share a few tricks I have learned on accessing paywalled newspaper articles and journal articles over the years.

I currently only pay for a physical Sunday newspaper for the Raleigh News & Observer (and get the online content for free because of that). Besides that I have never paid for a newspaper article or a journal article.

Newspaper paywalls

Two techniques for dealing with newspaper paywalls. 1) Some newspapers you get a free number of articles per month. To skirt this, you can open up the article in a private/incognito window on your preferred browser (or open up the article in another browser entirely, e.g. you use Chrome most of the time, but have Firefox just for this on occasion.)

If that does not work, and you have the exact address, you can check the WayBack machine. For example, here is a search for a WaPo article I linked to in last post. This works for very recent articles, so if you can stand being a few days behind, it is often listed on the WayBack machine.

Journal paywalls

Single piece of advice here, use Google Scholar. Here for example is searching for the first Braga POP Criminology article in the last post. Google scholar will tell you if a free pre or post-print URL exists somewhere. See the PDF link on the right here. (You can click around to “All 8 Versions” below the article as well, and that will sometimes lead to other open links as well.)

Quite a few papers have PDFs available, and don’t worry if it is a pre-print, they rarely substance when going into print.1

For my personal papers, I have a google spreadsheet that lists all of the pre-print URLs (as well as the replication materials for those publications).

If those do not work, you can see if your local library has access to the journal, but that is not as likely. And I still have a Uni affiliation that I can use for this (the library and getting some software cheap are the main benefits!). But if you are at that point and need access to a paper I cite, feel free to email and ask for a copy (it is not that much work).

Most academics are happy to know you want to read their work, and so it is nice to be asked to forward a copy of their paper. So feel free to email other academics as well to ask for copies (and slip in a note for them to post their post-prints to let more people have access).

The Criminal Justician and ASEBP

If you like my blog topics, please consider joining the American Society of Evidence Based Policing. To be clear I do not get paid for referrals, I just think it is a worthwhile organization doing good work. I have started a blog series (that you need a membership for to read), and post once a month. The current articles I have written are:

So if you want to read more of my work on criminal justice topics, please join the ASEBP. And it is of course a good networking resource and training center you should be interested in as well.

  1. You can also sign up for email alerts on Google Scholar for papers if you find yourself reading a particular author quite often.↩︎
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by apwheele on February 14, 2023  •  Permalink
Posted in ask me anything, Criminal Justice, Personal Productivity, scholarly, writing
Tagged

Posted by apwheele on February 14, 2023

https://andrewpwheeler.com/2023/02/14/getting-access-to-paywalled-newspaper-and-journal-articles/

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