Bibliographic record
Abstract
Hard Bop is a public artwork developed in collaboration with the San Francisco Mayors Office, Landscape Architects and Community Consultation, with the aim of regenerating a community space in the heart of Fillmore, San Francisco. Selected by peer review, via open competition organised by Sculpturesite, in the US, Canada and UK, the project is an example of a evolving research imperative of Atkin’s with the regeneration of public space through collaboration alongside designers and architects. Research for the work addressed the following questions:\n•How to regenerate a rundown area and reinstate it as a community meeting place, a location for performances and a hub for business growth.\n•How to create a landmark acknowledging the world-renowned Jazz heritage of Fillmore (Harlem of the West Coast) and link it to the present day.\n•How to redefine the locale through the process of regeneration, using children’s workshops: local radio interviews: ABC TV news items: exhibition of documentary film.\nthe neighborhood Fillmore Centre, in order to test and project concepts to the wider audience of the District\nResearch processes involved: Testing a range of reflective materials that could be perceived as ‘celebratory’; Consultation (British Stainless Steel Advisory Service) on the grade and type of stainless steel to withstand the urban & saline atmosphere of San Francisco; Testing different grades of polishing that will be reflective and simultaneously deliver low maintenance; Devising forms that translate recognizable references to musical rhythm into sculptural form: Using MAYA software to test how to reflect notions of spontaneity, which equate with musical rhythm and to further inform viewer interpretation of the sculpture with musical instrument-based references, such as Machine Head Keys, carved in granite; How to surmount the sculpture onto a water feature so that the confluence of audible water movement can intertwine with the rhythmic structure of the stainless steel reflective surfaces.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.836 | 0.636 |
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".