Out of Love and Desire: DIY Agency and Amateur Effort in the Public Realm
Bibliographic record
Abstract
Using the framework of a journey of learning, the author relates her own development toward producing community-engaged projects focused on do-it-yourself activity and a position advocating for more trust in amateur efforts. She addresses related subjects that build toward this position, with reference throughout to some of her own and community projects. First, she argues for the value of non-specialization and crossing disciplinary boundaries and problem-making. That is related to translation, code-switching and skill sharing as tools that enable one to operate across disparate fields. She gives examples of community efforts expressing collective intent that change urban space by understanding it as a field of play. This leads to a summary of theories of invention through play, especially risky play as a form of play that has many collective benefits. The valuing of risk, experimentation, and testing the limits of rules is then associated with creative processes and certain initiatives the author is involved with that deliberately challenge regulations, sometimes with an intention to oppose colonial systems. This leads to a discussion of the real benefits of citizen and amateur effort in building the character of social space and then an argument to view doing-it-yourself as both a right and a need. The article ends with a call to authorities to find more ways to trust and entrust amateur efforts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.039 | 0.105 |
| Scholarly communication | 0.019 | 0.010 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".