Introduction

A notion of meaning in context, of explanation and understanding through interaction.

Before I begin, I should point you to the initial motivational essay inspiring this proposal (here), and a literature review motivating the collection of better data to contribute to sociological knowledge of systems of beliefs (here).

Contributions to Science

Scalability and breadth of access

The researcher, once built, can be accessed and communicated with by anyone with an internet connection, and will be incredibly convenient for those with a smart phone.

Although smart phone users are not representative in one sense of the population, they reside in every country in the world, in every demographic slice whatever, and in many previously “hard-to-reach” contexts (citation).

The researcher could also collect data from an indefinite number of people at once, meaning an unprecedented scaling in sample sizes available. In an ideal scenario the Twitter handle @TheSociologists (possible name for what I have called “the researcher”) could have 1 million followers. For comparison, @wizkhalifa has 35 million followers. It could be carrying on a conversation with 10,000 of them at a given time. This large an adoption is not my expectation, at least not within the next few years, but it is possible outcome of such an algorithm.

Acts as an efficient and indefatigable qualitative researcher

The primary occupation of a researcher in Sociology is to ask people questions, watch what they do, what they make, in an effort to understand how the social infrastructure we are participating in maintains itself and the logic by which this infrastructure changes over time. And in order to do this, sociologists must always seek to understand the taken-for-granted social world of individuals. Society is structured insofar as it is meaningful.

But while the main occupation of the sociologist may be to understand, this means nothing if the sociologist cannot communicate this understanding convincingly. Methods for explaining sociological findings are elaborate, consisting of a nuanced collaboration between theory and data. In a written report, the researcher must navigate institutional practices of citation and framing, and presentation of results. The study must also be easily translated to “layman’s terms” for efficient incorporation into the community of knowledge in which they participate.

This hermeneutic praxis is exhausting, even more so for the qualitative researcher. The collection, interpretation, and analysis of qualitative interviews must be limited to a small set – of topics and individuals. One cannot survey the entirety of biography, experience, social networks, interaction with institutions, child rearing, cultural assimilation, with one study. Reality is at least as complex at this, supporting dozens of projects at once, but the interviewer must be direct.

Eliminate the researcher - researched dichotomy This tool not only enables the qualitative researcher to study large populations, it allows individuals to come to understand each other. When we are explaining ourselves to each other, it open-sources ‘sociology’, and … Makes it more about us understanding each other, and explaining ourselves to each other.

Sociology shouldn’t be an oligarchy of prescribed or used truths. Qualitative data collection leaves the analyst as a priveledged speaker of the reality of those they observe. One aspect of this priveledge is the separate space of the academic journal, separated by discourse, paywall, or lack of knowledge from the subjects of the study. When there is this separation, there cannot develop a dialogue between theory and reality, between the analyzed and the analyst. Bryman (1988) considers this topic in depth, and summarizes (p. 73): “What has proved to be disquieting to some commentators, both within and outside the qualitative approach, is whether researchers really can provide accounts from the perspective of those whom they study and how we can evaluate the validity of their interpretations of those perspectives.”

Theoretically relevant data

The interviewer would enables large-scale collection of theoretically important social data which have never before been collected systematically. How a person explains their beliefs and political stances, their prejudices and opinions of prejudice, –, all these would be collected in machine-readable form. This allows researchers to ask and answer empirically what before were purely theoretic.

  • Why do people mobilize?
  • What buttresses ideological, racial, or class divides?

Broader Impact

Giving society a tool with which to communicate

Humans’ potential for negatively impacting the planet is undeniable, and we are forced to consider for the first time in human history how we go about preserving the Earth’s ability to support human life.

In the up-swing of the technological age, as the world becomes increasingly complex, there is an urgent need for cooperation, communication, and understanding.

Echo chambers plague our ability to communicate effectively as a society. This is almost by definition, as echo chambers are just a stable lack of communication between groups. In some cases this cross-group communication is nearly impossible, either because of the emotional response it would arouse, or because the groups don’t understand the language of the other. It is not that the individuals don’t want to communicate, it’s that they have not the time, the energy, the language, the medium. People fundamentally wish to be understood, and we would all live in a safer and more just world if we understood each other.

A full understanding of the conditions under which a product or service is being produced - the true sacrifice and costs (or perhaps benefits) of this production chain - enables the consumer to improve the social constructions under which we all live On the flip side, ideological manipulation and misinformation is the most effective tool in maintaining unjust and potentially disasterous social constructions.

An intermediary (not quite a broker)

Communication is greatly facilitated by an intermediary. That is, a translator, one who understands and explains to both sides, learning in the process. This translator is instrumental in true globalization, in the sense of becoming one (Jijon 2019).

Typically, one person constructs an explanation specifically for another person, or at the very least for a type of person. Explanation is best done in person, one-on-one, as it allows for clarification and questions, and these opportunities make this explaining-to much more direct and effective.

Yet interactive explanation (and understanding) is an extremely scarce resource. A person has room for only a few people they can come to understand, and spend time explaining themselves to. And each of those people have a few people they come to understand. For most, this sparser social network does not reach very far in social space. Those which are close emotionally are most often close spatially, creating a natural clustering. The broker, the facilitator of an understanding between those who otherwise would never understand each other, can bring new understanding, although rarely breaching the walls of an echo chamber.

Methodology

The component speech acts of the qualitative interviewer

An interview can be usefully understood as a sequence of speech acts, of intents and expectations embedded in a commonly understood pattern (c.f. Austin 1975). Conversants take turns, each turn with some intent. In a question the intent might be to elicit information or to understand a word or phrase better. In clearing up some verbal miscommunication there is a defined ritual we observe. In each statement we occupy some known position in the well-trodden conversational artifact. The full flow of conversation in a clarification is depicted below:

This network among states of expectation in conversational flow is self-contained, independent from the network representing talk about the weather, or asking about another’s family history. In Wittgensteinian terms this network is a language game (see Grayling 2001, 83). Because each of these games is separable from the rest, independent and self-contained, programming a qualitative researcher becomes a decomposable task. Conversation as a complex and varied structure can be expressed in terms of discrete modules. Our task here will be to break the competencies of a qualitative interviewer into its component speech acts, and code them.

Constructing a Python package for enacting speech act networks

I’ve set about accomplishing this goal through a conceptualization of language as a game , a sequence of speech acts , and have represented these games in terms of objects in Python. I program some “ways of communicating”, routines which know how to understand some large collection of what surface forms means in terms of speech acts within a language game. One of the most important “games” I’ve created is that of clarification (shown in the figure above). This game is initiated by the algorithm when the algorithm doesn’t understand something the person said, asks for clarification of the part of what they said it didn’t understand, and either eventually gives up understanding or understands the person’s explanation. If the algorithm understand what the person meant to say through this process, it updates its bank of “ways of communicating” for future use. By mirroring the code for one side of this game, we get the other. For example, because the algorithm knows how to express misunderstanding, it also knows how to recognize when misunderstanding is expressed by the other, and is able to participate in the other side of this language game.

Relatively independent functional modules

Continuous real-world testing

Hiring undergraduates to code

This project is ideal for completing with skilled student coders. Tasks provided are bite-sized, and can be completed in full by a single student in a semester of working 9 hours per week.

I’ve collected a petition of 50 students who are interested in working.

The undergraduates agreed to the project described below

This summer I am hiring programmers to help me with my dissertation. Applicants should have experience in Python and object-oriented programming, the more past experience the better.

My idea is to create a completely new way to interview, which would allow researchers to collect deep understandings of many people in machine-readable form. More concretely, I’m developing a Twitter handle which can conduct interviews over PM as skillfully as would a sociology graduate student. This “researcher” would be able to ask clarifying questions, follow up on previous conversations, wonder about how your brother is doing, actively trying to understand who you are and what you care about. I really care about this project and think it could be revolutionary, not only for Sociology, but for people’s understandings of each other more generally.

If you’re interested in participating Summer 2020 send an email to . The position would be part time (10 hours per week) and paid $15/hour.

I would need X +- 50 coder hours to complete Z1 Z2 Z3

Critiques and downsides

References

Austin, John Langshaw. 1975. How to do things with words. Oxford university press.

Bryman, Alan. 1988. Quantity and Quality in Social Research. New York, NY: Routledge.

Grayling, A. C. 2001. Wittgenstein: A Very Short Introduction. Oxford: Oxford University Press.

Jijon, Isabel. 2019. “Toward a Hermeneutic Model of Cultural Globalization: Four Lessons from Translation Studies.” Sociological Theory 37 (2): 142–61. https://doi.org/10.1177/0735275119850862.