Mid America Print Councilâs National Conference, Themed Portfolio "Reverse Watching"
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The theme of this portfolio, Reverse Watching, is Inverse Surveillance and Targeted Sousveillance (Terms coined by Steve Mann, Professor, University of Toronto). Inverse surveillance systems are ones that monitor, study, investigate, or record surveillance systems or those doing the surveillance. This has included, mapping CCTV locations, monitoring police activities (e.g. filming), reacting to privacy issues, or control of information online (e.g. site tracking). It may also be countering the secret nature of surveillance and making information more accessible. Targeted Sousveillance refers to the watching by one individual of other individuals or groups, specifically rather than randomly. These individuals or groups might themselves be a promoter of surveillance, thus the watched, watching the watchers. Participants in the portfolio were asked to consider the increasing role of surveillance in our society and specifically how Inverse Surveillance and Targeted Sousveillance can, or should be, used to counter or draw attention to its effects. Could the acceptance of surveillance lead us to a society with less freedom? Should we change our behavior now to take us in a different direction? How should we navigate its effects?\nParticipants: Edward Bateman, Justin Diggle, Jeffrey Dell, Stefanie Dykes, William Fisher, Christopher Ganz, Ruthann Godellei, Stephanie Hunder, Brian Johnson, Ron McBurnie, Johanna Paas, Mary Robinson, Jim Sconyers, Chadwick Tolley
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.
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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it