(Dis)enchanted Walking - Publications and Exhibition: walking and media arts a developing approach
Bibliographic record
Abstract
Two public walking arts projects, Honouring Esther and Sweet Waters, developing a critical walking arts and media practice bringing past injustices into present consciousness generating contemporary social justice resonances.The live work offers an iteration of walking-with (Sundberg 2014) as a non-confrontational approach attending to obscured and reluctant heritage (Tomory 1997). This item documents developing the walking/social media process. A documentary video record of the installation element of an exhibition showing work from Honouring Esther and Sweet Waters Publications exploring earl.y and continuing development of the creative practice as research process: reporting on a walking and social media workshop at the site of the 2012 Olympic Games in East London for the Living Maps Network, and most a recent publication following participation in a partnership programme with Huron College, Ontario exploring the theme of reluctant heritage and hidden history walking the spaces and silences of slave-ownership. Citations for the included articles: White, R (2016) 'Social media trails, mapping and mashing memories at the Queen Elizabeth Olympic Park.' Livingmaps Review, 1 (1). ISSN 2398-0338 Reid-Maroney, N, Bell, A, Brooks, N, Otele, O and White, R (2019) 'From 'Uncle Tom’s Cabin' to “Countering Colston”: slavery and memory in a transatlantic undergraduate research project.' International Public History, 2 (1). 020190006. ISSN 2567-1111
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.029 | 0.007 |
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".