Bibliographic record
Abstract
The proliferation of the automobile as a personal environment and the construction of freeways in the North American urban landscape during the mid to late 20th century are often blamed for noise and air pollution, the sprawling homogeneous metropolis, the erosion of the neighbourhoods, streets and communities, and a generally destructive quality of life. \n \nThe construction of Seattle’s I-5 freeway during the 1950s was successful in creating and expanding commuter accessibility for Seattle’s drivers. But in the process it created a border, severing urban communities from one another at a localized level. OnRamp, seeks to reconnect the communities of Capitol Hill and Eastlake through an urban trail design. The intention is to incorporate this trail design into Seattle’s existing historic City Parks system to create a continuous chain of navigable open space in which to wander. \n \nThe importance of urban freeways in our contemporary cities are often overshadowed by the physical and cultural separations they have created in the urban landscape. When considering freeways, we should resist the impulse to associate them with the ills of society. They are a product of a cultural fascination with prosperity, mobility, privacy and the pastoral. They represent a collective will to create a more satisfactory way of life. They are relics of the past; sculptural artefacts that inform us of where we have been and where we are going. \n \nThe purpose of OnRamp is to demonstrate how the distinct ecologies of urban freeways and the residual space surrounding them can be creatively entwined with the structure of the city.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.791 | 0.585 |
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".