Commoning for Fun and Profit: Experimental Publishing on the Decentralized Web
Bibliographic record
Abstract
The World Wide Web is dominated by big tech and seemingly endless scandals after a decade of growing distrust about the role technology and the Internet play in our society. As a result, there are calls for the creation of alternatives to the existing platforms and infrastructures. One such alternative is a decentralized web (DWeb) where users have control of their data and decisions. This paper presents a collectively-produced organizational autoethnography of the development of an emerging tool for publishing on the decentralized web and the magazine using it to contribute to the digital commons. Three key themes emerged: 1) how a commons-based understanding of boundaries supports participation in a broader ecosystem; 2) the ways commoning as a frame deepens engagement as opposed to a passive model of a digital commons platform; finally 3) the need to re-assess how a cohort lab model that structured the work feeds back into larger goals. From these findings, we reflect on how this project fits into a maturing DWeb ecosystem and what possibilities for social transformation are present in transitional forms of commons. We discuss the pressing need for CSCW and adjacent research communities to participate in the design of, and debates over, the new computing paradigms developing out of this wave of decentralized technologies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".