OPEN SOURCE
Open source proved that when people can inspect, contribute to, and freely use shared work, the collective output surpasses what any closed system can produce. Its operating model of open inspection, open contribution, open access, and work that compounds with every participant built infrastructure the world depends on. R:EL applies that same model to a different kind of source material. In open source software, anyone can inspect the code, contribute improvements, and deploy the result. In R:EL, anyone can inspect the archive, contribute their experience, and use the collective data to advocate for change. The operational logic is the same. The difference is what is being shared. Code is impersonal and infinitely reproducible. The lived experience of survival spending is intimate and given in trust. That difference demands something open source never needed: custodial protection of the contributions themselves — someone protecting what people share, because it is intimate and given in trust — while keeping participation, the archive, the vocabulary, and the outcomes fully open.
OPEN SOURCE SOFTWARE
OPEN Source code: anyone can inspect
OPEN Contribution: anyone can improve
OPEN Deployment: anyone can use
OPEN Compounding: each contribution strengthens the whole
OPEN Governance: community maintainers shape direction
OPEN Source material: code, impersonal, reproducible
R:EL
OPEN Archive: anyone can inspect
OPEN Participation: anyone can contribute
OPEN Outcomes: data serves communities
OPEN Vocabulary: each submission expands the emotional taxonomy — the range of emotions the archive can name
OPEN Governance: communities shape access and priorities
OPEN Source material: lived experience, intimate, given in trust
When someone submits a receipt to R:EL, they are sharing more than a transaction. They are naming what it felt like to stand in that checkout line, to make that choice, to carry that weight. That act of naming is done in trust. It is intimate. It is willingly given. And because it is willingly given, it is sacred.
The infrastructure that holds those contributions has a custodial responsibility — a duty to protect what people have trusted it with. R:EL protects its codebase not because it is proprietary but because it is the architecture of a space where people do that naming. You do not open-source the room. You keep the door open and you protect the walls.
R:EL performs three acts of functional reassignment — it takes three things that already exist and changes what they do. The receipt is reassigned from corporate accounting tool to civic emotional archive. The AI is reassigned from commercial content engine to an anti-extractive emotional vocabulary system — a system that helps people name what they feel about spending, trained to refuse clinical language, honor cultural specificity, and locate economic harm in systems, not individuals. And open source is extended from a framework for sharing code to a civic framework for sharing lived experience, with the addition of custodial protection that code does not require, because code is not intimate but naming your economic survival is. All three take something globally understood and restructure it for the well-being of the people it affects. All three are Arte Útil — art that functions as civic infrastructure.
COMMUNITY GOVERNANCE
The emotional tagging taxonomy — the list of emotions people can choose from — along with data access policies and reporting priorities are governed by community input, not a single author. The initiator builds the infrastructure. The users shape its function.
INSTITUTIONAL PARTNERSHIPS
Designed for adoption by mutual aid organizations, food policy councils, public health researchers, and community land trusts. The data serves those who need it, not those who profit from it.
DATA ETHICS
All submissions are anonymous. No accounts, no tracking, no behavioral profiling. Data serves the public. This archive is civic evidence, held in trust. Not for the retail analytics and financial systems that capture economic life, profile the people living it, and monetize that data back against them.
NO MONETIZATION
The archive does not sell data, serve ads, or profile behavior. The emotional and economic contributions people make to this platform are not commodities. They are civic evidence — public documentation, held in trust, for the communities that need it.
PROFESSIONAL ROLE
ANTI-EXTRACTIVE ARCHIVIST (AE : A)
(Against corporations profiting from people's economic data. Against private ownership of what people live through economically.)
One of the goals of this project is to create work that does not yet exist because no institution is designed to pay for it. Someone has to maintain the infrastructure of collective knowledge that corporations refuse to build and governments fail to fund. The Anti-Extractive Archivist (AE : A) is that role: part community researcher, part data steward, part civic technologist, part systemic investigator.
A corporate data analyst manages data, produces reports, and identifies patterns. The AE : A does something fundamentally different. Where the corporate analyst asks what people are buying, the AE : A asks what the true cost of survival is: not only the emotional weight of standing in a checkout line, but what that weight reveals about the systems people are surviving under. The emotional documentation is the entry point. What it exposes is material: which communities lack access to affordable healthcare, clean water, breathable air, and livable infrastructure. Where environmental burden falls. Whose neighborhoods are polluted and whose are protected. Which populations carry compounding economic distress that manifests not only as stress and sacrifice but as chronic illness, shortened life expectancy, and generational poverty. The AE : A reads these patterns because the archive makes them legible in ways no corporate dataset can: through the language people use to describe what it costs them to live. This is not data analytics with different allegiance. It is a different practice entirely. The emotional vocabulary the archive collects is evidence of structural conditions that corporations, governments, and policy systems produce and maintain. The AE : A traces that evidence from the individual receipt to the systemic failure: from the dread of watching prices rise beyond what a household can absorb to the trade policies that caused it, from a caregiver calculating which meals to skip and which bills to delay to the healthcare infrastructure that abandoned them, from entire neighborhoods where nothing is affordable to the economic and environmental policies that manufactured that scarcity. The role develops new methods for understanding how economic injustice operates at the level of lived experience, produces public research that names these systemic conditions rather than individualizing them, and brings that evidence to the organizations, policymakers, and communities positioned to act on it.
The AE : A is also responsible for the continuous development and improvement of R:EL itself: refining the emotional taxonomy — the vocabulary of emotions the archive uses — as new contributions reveal gaps, evolving the archive's analytical tools to surface patterns that matter to communities, and ensuring the infrastructure remains aligned with Arte Útil principles as it grows. The role does not just maintain what exists. It builds what should exist next. It is more than a job. It is a civic practice of making visible what economic systems are designed to hide: not only the emotional cost of surviving under those systems, but the material conditions they produce. Who gets healthcare and who does not. Which environments are polluted and which are protected. Where clean water is accessible and where it is not. How city infrastructure distributes resources along lines of race, class, and colonial history. How corporate and government policy decisions register not in spreadsheets but in the bodies and daily lives of the people those decisions affect. The archive documents these conditions every day through the language of the people living them.
The role demands the same rigor as academic research, the same technical fluency as data science, and the same relational care as community organizing, but it exists in a space none of those fields currently fund because the work itself is new. The argument for compensation is the same argument R:EL makes about the receipt: the labor is real, it is invisible, and the fact that no system is designed to pay for it is a structural failure, not a reflection of its value. Work that requires this much care and attention to detail requires someone who truly cares, and it is precisely because of that care that they should be compensated.
The open source model makes this role possible. Not open source as the technology industry defines it, but open source as R:EL redefines it: open participation, open archive, open vocabulary, open outcomes, and custodial infrastructure — infrastructure maintained in trust on behalf of the people who contribute to it. The AE : A is the custodian. R:EL is publicly accessible and free to use, but its data is not for sale and its labor is not for hire. Future funding paths include public interest technology fellowships, arts council and foundation grants, university research positions, community funded models where the people who contribute to the archive also sustain the person who maintains it, commissioned research from mutual aid organizations and food policy councils, and institutional adoption where R:EL becomes part of an organization's civic infrastructure. This project makes the case that this role should exist, and that the communities it serves should be the ones to fund it.