Bibliographic record
Abstract
Streetnotes (2011) 19: i-iii ISSN: 2159-2926 i Editorial Board Editor David Michalski, University of California, Davis michalski@ucdavis.edu Editorial Board Lois Ascher, Wentworth Institute of Technology Claudia Brazzale, Rutgers, The State University of New Jersey Godefroy Desrosiers-Lauzon, Institut National de la Recherche Scientifique Derek Fenner, Bootstrap Press Hitomi Iwasaki, Queens Museum of Art Tara Milbrandt, University of Alberta, Augustana Blagovesta Momchedjikova, New York University Samuel Neural, Universite Lyon 2 Mark Nowak, George Washington College Ines Rae, University of Plymouth Marta Rabikowska, University of East London Adam Siegel, University of California, Davis Joseph Trotta, Goteborgs Universitet Aim and Scope Streetnotes is a peer-reviewed biannual journal for the interdisciplinary study of the city, its lifeways and social relations, with a special concern for the cultural and aesthetic forms that arise through its traffic. We publish qualitative sociology, critical essays, documentary photography, poetry and visual arts informed by the ethnographic exploration of contemporary and historic urban forms. Our name, Streetnotes is a turn on the word ‘fieldnotes’, as such our journal seeks methodological innovation and critical engagement through works which lay bare the poetics of discovery, display and analysis of street observations. Towards this end we publish work of seasoned and aspiring scholars, social scientists, artists, photographers and poets engaged in creative ways of making sense of, and questioning the familiar and strange of urban life in the effort to build empirically based social theory. To nurture the humanistic exploration of the city as a social form, Streetnotes seeks to develop through its publications a popular ethnographic tradition, one that encourages the mass reflection and critical grasp of the concrete matrix of urban social life. Peer Review Process: All work submitted to Streetnotes undergoes double-blind review by at least two experts chosen by the Editorial Board for their knowledge and experience. The selected reviewers provide feedback on the work and make recommendations to the editors. The Streetnotes Editorial Board makes final decisions on whether or not the article is suitable for publication, whether or not the work is in need of revision, or whether or not the work is appropriate for the aims and purposes of the journal. http://escholarship.org/uc/ucdavislibrary_streetnotes
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.092 | 0.042 |
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; both teacher heads agree on what is shown here.
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".