Making our world : the hacker and maker movements in context
Bibliographic record
Abstract
Jeremy Hunsinger/Andrew R. Schrock: Introduction - Andrew R. Schrock: Section I: Histories Introduction - T. Philip Nichols/Debora Lui: Learning by Doing: The Tenuous Alliance of the and Education Reform - Molly R. Sauter: Kevin Mitnick, The New York Times, and the Media's Conception of the Hacker - Yasuhito Abe: Making Civic Media in the Post-Fukushima Japanese Media Ecology - Rhea Vichot: Project Chanology and the Formation of Anonymous as an Activist Movement - Andrew R. Schrock: Section II: Politics Introduction - Nathanael Bassett: Conscientious Hacking and the Weak Collective - Arne Hintz: Policy Hacking: Opening Up the Code of Media and Communications Regulation - Morgan Currie: Hacking Administration-A Report From Los Angeles - Sebastian Kubitschko: Why Locality and Presence (Still) Matter for Political Activism - Jeremy Hunsinger: Section: III: Organizing Introduction - Alexander von Lunen: Basteln, Tinkering, and Bricolage: A Cultural History of Hacking - Jennifer Maher: Women's Hacking of the Poison Gift of Free/Libre/Open Source Software - Alison E. Vogelaar/Charlotte M. McKernan: Making Space for a Revolution: Occupy Wall Street as a Maker Movement - Ann Light: The Detente Model of Managing Divergent Values in the Maker-Sphere - Jeremy Hunsinger: Section IV: Case Studies Introduction - Pip Shea: Hacker Agency and the Raspberry Pi: Informal Education and Social Innovation in a Belfast Makerspace - Nicholas Balaisis: Hacking as a Way of Life: at the Margins of Global Digital Culture - Xin Gu: The Paradox of Maker Movement in China - Karen Louise Smith: Our Community Hacks: Exploring Hive Toronto's Open Infrastructures - Andrew R. Schrock: Afterword: Hackers and Makers are Ordinary.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".