Spatial Profiling: (After Margaret Dragu's <i>Eine Kleine Nacht Radio</i>)
Bibliographic record
Abstract
May 01 2014 Spatial Profiling: (After Margaret Dragu's Eine Kleine Nacht Radio) Francisco-Fernando Granados Francisco-Fernando Granados Francisco-Fernando Granados is a Guatemalan-born, Toronto-based artist, writer, and educator working in performance, video, drawing, cultural criticism, teaching, and curatorial practice. He has performed spatial profiling … in Toronto, Vancouver, and Helsinki. Search for other works by this author on: This Site Google Scholar Author and Article Information Francisco-Fernando Granados Francisco-Fernando Granados is a Guatemalan-born, Toronto-based artist, writer, and educator working in performance, video, drawing, cultural criticism, teaching, and curatorial practice. He has performed spatial profiling … in Toronto, Vancouver, and Helsinki. Online ISSN: 1537-9477 Print ISSN: 1520-281X © 2014 Francisco-Fernando Granados2014 PAJ: A Journal of Performance and Art (2014) 36 (2 (107)): 58–61. https://doi.org/10.1162/PAJJ_a_00197 Cite Icon Cite Permissions Share Icon Share Facebook Twitter LinkedIn Email Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Search Site Citation Francisco-Fernando Granados; Spatial Profiling: (After Margaret Dragu's Eine Kleine Nacht Radio). PAJ: A Journal of Performance and Art 2014; 36 (2 (107)): 58–61. doi: https://doi.org/10.1162/PAJJ_a_00197 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll JournalsPAJ: A Journal of Performance and Art Search Advanced Search © 2014 Francisco-Fernando Granados2014 Article PDF first page preview Close Modal You do not currently have access to this content.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".