“We should all feel welcome to the park”
Bibliographic record
Abstract
This article investigates the potential for intergenerational public space in the Westlake neighborhood of Los Angeles. Through a series of site observations, focus groups, interviews, thick mapping, and participatory design exercises, we work with 43 youth and 38 older adults (over 65), all residents of Westlake, to examine their public space use, experiences, and desires, and identify where the two groups’ interests intersect or diverge. We explore the potential for complementary approaches to creating intergenerational public space using the principles of Universal Design. In doing so, we emphasize the importance of taking an intersectional approach to designing public space that considers the multiple, often overlapping identities of residents of historically marginalized communities predicated by disability and age, in addition to race, class, and gender. Our findings yield insights for creating more inclusive and accessible public spaces in disinvested urban neighborhoods as well as opportunities for allyship between groups whose public space interests have been marginalized by mainstream design standards. Read the full article in accessible html-format here.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.012 | 0.012 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.017 | 0.005 |
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".