Digital Materiality as Imprints and Landmarks: The case of Northern Lights
Bibliographic record
Abstract
In this paper a case is made concerning how important levels of media technology and new interactive textures affect urban landscapes. The case is based on experiences and empirical examples from a Scandinavian city (Northern Lights) in which levels of interactive infrastructures, mediated spaces, and places, are high, and in which accessibility and social inclusion traditionally have been strong components in societal and systems design. Our designerly approach discloses some of ways that the city is enacted by a new digital materiality. This materiality can only bee disclosed if the relationship between the city and ICT is understood as a meaningful whole – a totality – in this text illustrated by the notions of landmarks and imprints. Based on our case we suggest that it is possible to employ an ethical dwelling reflecting the endless, active and ongoing responsibility for the city and its interactive textures in everyday life.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.042 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".