Bibliographic record
Abstract
“Adapting Snäckan 8” aims to investigate material and immaterial value while transforming an existing built structure. Current development plans seek to demolish and replace the existing building by a new, 10 meter wider, 4.5 meter taller building of office spaces; increasing the scale of the Klara quarter once more, just as during the Norrmalm Regulation historically. Excluding both: plans for housing, as well as the so called “Culture House”. A space that included a café, a library and a cinema, for everyone, including especially the homeless people of Stockholm.Accompanied by a notion that when we demolish built structures, not only do we demolish material, but also social structures that have been built up over time; the ecological aspects of adaptive re-use are expanded by social urgency. In light of the housing crisis and increasing social segregation as well as the development of the pandemic, the accessibility of a home is now perhaps more pressing than ever. This project therefore aims to provide affordable, inclusive mixed-use living within the city centre, adapting Snäckan 8 to changing rhythms and patterns of daily life. Thereby hoping to continue writing the story of Snäckan 8, rather than erasing it.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.048 | 0.014 |
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".