Author Archives: Martin Glick

Bio

Martin Glick is a Graduate Student at the CUNY Graduate Center pursuing an M.A. in Digital
Humanities. He has a B.A. in Philosophy from City College (CUNY), an M.A. in Philosophy at
Birkbeck College (University of London), and conducted independent research at the Chair for
Legal and Social Philosophy at the University of Göttingen from 2013-2017. He is currently a
Metadata Associate at Callisto Media, which is a data-driven publishing startup. Previously he
worked at John Wiley & Sons in the Editorial department. From Northeastern Pennsylvania, he
now lives in Brooklyn.

His favorite movie is Alien, and he wrote a chapter about it in a volume for the Blackwell Philosophy and Pop Culture series.

Project Update

I created a dashboard in Trello to act as a storehouse for Class Notes, Deadlines, and Meetings that people can share notes and links. Eventually a Gantt chart will be placed here as well.

To continue my post on “thought-in-progress” through screen sharing. Joanne and Eva were gracious enough to work through some of the data wrangling in Python before our very eyes. It was a unique experience that allowed us to peer into the mind of someone working through a problem. The benefit of working in a group project using skills we have honed over the last few years in school or at work is that we are still working through tools we have learned to use. In that sense there is still a testing out of what works best, and thankfully no one in the group is shy about presenting works in progress. In this sense we all get to learn what a JSON file is, how to successfully link up datasets in Github, and what a successful wireframe for a website looks like. 

We took to heart the presentation given by Dr. Lisa Rhody, when creating the collaborator’s agreement. It seems to me that sometimes the boundaries of responsibility can become a little muddled. Especially in cases where members of the group are enthusiastic about being involved in other parts of the project. It only speaks to the benevolence of the members of my group. We have settled on dividing up the work according to established strengths, but are considering recording parts of the workflow for the edification of the other members. Through these videos we are able to share knowledge, and introduce others to at least the fundamentals of programming or UX/UI design.

The advice to centralize the role of Outreach was well received by our group, and I was appointed as the person to spearhead these developments. There does seem to be some work necessary in one crucial aspect, highlighted by Joanne: Where is the boundary between simplifying and potentially losing nuance regarding the outcome of a case. – Does the process of aggregating this data lose nuance? Since not every case is the same (in many different ways, length, people involved, location) We want to avoid a flattening/distortion. To get to the heart of this we intend to meet with Micki who has also dealt with case law to some degree in hter Kissinger Project; and understand better the real-world ramifications of contending with historic and political documents.

 

FairCopy NYCDH Presentation review

One upside of the pandemic forcing communication between people to be conducted online has been that it fosters an environment of openness that heretofore was thought impossible. Lectures and conferences from Oxbridge schools are now made public to anyone with the Zoom link, research clusters like the Berkman Klein Center are focusing on international cooperation regardless of the time zone, and screen sharing through video conferencing tools allows an over-the-shoulder view of how to use software tools from global developers. This last point was well represented by the team at FairCopy, and inspired in my mind a suitable tool for a project that I had been kicking around in my head.

 

FairCopy is a transcription tool which pairs up images and text side by side to facilitate the transcription and commenting of scanned images. What I appreciated from the presentation which guided us through downloading a Library of Congress file and ingesting it into the program was the intuitive and the process of starting to get text into the editor was quite seamless.

 

Below is an image of the UI

I have been playing around with the software and hope to transcribe some Journals of the Cybernetics theorist W. Ross Ashby. His journals have had select summaries and keywords transcribed then linked in the webpage to enable the Search function, but a complete transcription has not been undertaken. 

Below is an image of the Journals online.

I want to take up the idea that screen-sharing has eased us into the ability to witness “thought -in-progress”. It struck me during this presentation during the QA session when the developers fielded questions and worked them out in real-time, that because we are in our respective homes, there is a comfort with working things out in front of others. A comfort that we maybe wouldn’t have if we were in a shared space away from our routine surroundings. The advantage is that the attendees get to bear witness to the kinds of thoughts and step by step working out of problems. We are invited into the mind of someone else. That’s what interests me so much about Journal entries. For me, these are snapshots frozen in time of this “thought-in-progress” that we are luckily privy to, due to our decentralized mode of communication. 

 

A person comfortable in their own home will allow the full unweaving of a process, when presented with an idea. Historically what has happened in the pages of a Journal, but now a screen-shared view of an expert working with software offers a similar insight.

Freedom Of Speech: Data Management Plan

1. Data Collection

  • What data will you collect or create?
    • Our metadata about court cases, and our initial filtering, comes from the Washington University in St. Louis (WUSTL) law school database, also known as The Supreme Court Database (SCD). The dataset is comprised of two .csv files that we have downloaded which cover: (1) cases up until 1945; and then (2) post-1945. These two .csv files have been stitched together in a chronological manner. Each case then has the actual, court-published opinion texts as well, scraped from the Justia website and attached to the dataset.
  • How will the data be collected or created?
    • After having downloaded our data from the SCD, the next step is to filter by First Amendment. The download produced a larger dataset than we are actually interested in, so the next step is to filter for cases that address the Freedom of Speech specifically. These cases will be taken from the book Landmark Supreme Court Cases: The Most Influential Decisions of the Supreme Court of the United States (Vol. 3. 2nd ed.) by Richard A. Leiter and Roy M. Mersky. In its complete form, the data will be a JSON file with nested features.
  • Is it possible to regenerate the data? What are the implications for your research if the data are lost or become unusable later?
    • It is possible to regenerate our data by recreating the steps mentioned above and rescraping Justia for the opinion texts. We have backups of all of the processes we have created in order to get our final, usable dataset.
  • What are the tools or software you will be using to create/process/analyze/visualize the data?
    • We will be using a Jupyter Notebook to create, process, and analyze the data. Some visualizations will be sketched out using a mixture of matplotlib/seaborn for initial topic modeling/text analysis, and then reimagined in d3.js.

2. Documentation and Metadata

  • What documentation and metadata will accompany the data?
    • We will use README.md files to document our data’s features and the processes we work with. These processes include: combining SCD’s codebook with the codebook we create for the features we generate in the process of building out the existing database; processing documentation of cleaning, scraping, and filtering; and linking to SCD, Justia, and the textbook we’re using for analysis purposes (Landmark Supreme Court Cases). 
    • In order to ensure good project and data documentation, we will be taking notes throughout the creation, cleaning, and processing phases and then compiling those notes into README files.
    • Each of us, with respect to our roles in the project, will be responsible for an aspect of data management.
    • We will use categorical descriptive terminology in order to name our directories and files, and because our data is already mostly created, we will be following the standards of the already-created datasets.

3. Ethics and Legal Compliance

  • How will you manage any ethical issues?
    • Managing ethical issues largely entails deferring to experts when possible—especially through Landmark Supreme Court Cases—rather than deciding ourselves what “counts” as a landmark case. We will also aim to be transparent about where our data is from and any decisions we have made in curating it. 
  • How will you manage copyright and Intellectual Property Rights (IP/IPR) issues?
    • The SCD allows us to download and transform the data, with attribution. Regarding the Landmark Cases textbook, we will be reaching out to the publisher in order to request permission to use the content therein.

4. Storage and Backup

  • How will the data be stored and backed up during the research?
    • To use Stephen Zweibel’s language, we will use Github for “far”, flash drives for “near,” and our computers for “here.” Doing this should allow for sufficient storage. Regarding backup, each of us will back the data up locally, as well as on flash drives just in case.
  • How will you manage access and security?
    • Our Github repository/organization is closed to the public in terms of who can edit and manage the repository, so only our group can control it. The repository can still be forked, but the root data will not be mutated.

5. Selection and Preservation

  • Which data are of long-term value and should be retained, shared, and/or preserved?
    • After cleaning, processing, and finalizing the dataset, we will be keeping it in our Github repository. We will be keeping it there for the foreseeable future.
  • What is the long-term preservation plan for the dataset?
    • Github will also be used for long-term preservation.

6. Data Sharing

  • How will you share the data?
    • We will make the data immediately available upon upload, via the Freedom of Speech* site. The data itself will be a public, raw dataset available through Github.
  • Are any restrictions on data sharing required?
    • Our case data is in the public domain, but we may have to restrict our data if we are given a limited license by the publishers of the Landmark Cases textbook.
    • **need to check copyright**
  • Who is your possible audience? Who may use the data now, or later?
    • Our possible audience would be: any audience interested in First Amendment rights; law students who specialize in Constitutional Law; and members of the general public who want to know more about the fundamentals of legal studies; we also hope to reach a more “casual” or amorphous audience on social media platforms like Twitter, where Freedom of Speech is a relevant/hot topic.
  • What tools/software are required to access your data?
    • No special tools or software are required to access the data; if the user has a web browser, they can access it through our Github page, which will open the data in a new window.

7. Responsibilities and Resources

  • Who will be responsible for data management?
    • Each member of our team will exercise due diligence in implementation of the standards outlined above.
  • What resources will you require to deliver your plan?
    • We have all the resources we need in order to deliver our plan: Discord for communication, Jupyter Notebooks + Python for code and processing, Figma for design ideation and UX/UI wireframing/prototyping, Observable Notebooks for prototyping visualizations in d3, and Github for storage and hosting.
Link

Skills – Martin G

M.A. in Philosophy and working at a publishing startup. Previously I worked at Wiley so I have a good handle on manuscript editing and article revisions. I’ve used in Tableau to present data points as well.

Project Management: At work I oversee a production schedule of hundreds of books using Excel and Smartsheets and their assets in a DAM (Widen). I suppose I would be able to bring to a group a sold sense of organization.

Developer: I taught myself Gephi and AntConc. No coding experience to speak of but I’m quite handy at quickly learning the ins and outs of text analysis software. Voyant Tools is another I’m fond of. 

Design/UX: Little to none. 

Outreach: I like working with Vendors and those who have a shared interest in the success of project. But reaching out and cold-calling (emailing) to drum up motivation towards a goal may not be my strong suit.

Bonus: I worked with Evgeny Morozov’s team to help create https://www.the-syllabus.com/. I conducted content review of thousands upon thousands of articles on the web to train an algorithm.