Emergent Graphics: Graphic communication as a systems change agent
Bibliographic record
Abstract
Graphics, whether you call it ‘design’ or ‘communications’ is a system that has emerged at various times, from various societies, and through various media, but with a common mode of practice. We communicate, using visual means (oh so many diverse means). And we carry out these communications in ways that are diverse in the visual codes that are applied, but commonly with a small range of intended outcomes: to explain, to demystify and to reduce the complexity of socio-cultural systems too baroque for the citizen to operate without help. Sometimes these systems are markets, sometimes cities, but graphics is there to help. While these operations have frequently been exploited to explain the ways of government to the governed, and then to sell merch’ to them too, it doesn’t have to be used that way. The practice of graphics is a process that is agnostic as to the thing being communicated: in 1919 El Lissitzky promoted the Russian Revolution, in 1924 it was Pelikan Ink. The practice of graphics can move beyond servicing vested interests and be a powerful tool in engaging in dialogic design to address global problems. The paper uses Meadows’ 1999, Leverage points: Places to intervene in a system, as a structure to consider the clustering of graphic communications practice around certain functions of communication and control, with the intention of using its accumulated practice as a lever for large scale social change.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.030 |
| Scholarly communication | 0.015 | 0.009 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".