Bibliographic record
Abstract
April 01 2020 Palmyra, or the Construction of Ruin Andrew Scheinman Andrew Scheinman Andrew Scheinman is a writer and spatial practitioner whose work centers on architecture, media and the politics of memory. He received a Master in Design Studies with distinction and the Dimitris Pikionis Award from the Harvard Graduate School of Design in 2019 and currently works as an editor at the Canadian Centre for Architecture in Montréal. Search for other works by this author on: This Site Google Scholar Author and Article Information Andrew Scheinman Andrew Scheinman is a writer and spatial practitioner whose work centers on architecture, media and the politics of memory. He received a Master in Design Studies with distinction and the Dimitris Pikionis Award from the Harvard Graduate School of Design in 2019 and currently works as an editor at the Canadian Centre for Architecture in Montréal. Online Issn: 2572-7338 Print Issn: 1091-711X © 2020 Andrew Scheinman2020Andrew Scheinman Thresholds (2020) (48): 62–73. https://doi.org/10.1162/thld_a_00711 Cite Icon Cite Permissions Share Icon Share Twitter LinkedIn Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Search Site Citation Andrew Scheinman; Palmyra, or the Construction of Ruin. Thresholds 2020; (48): 62–73. doi: https://doi.org/10.1162/thld_a_00711 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search nav search search input Search input auto suggest search filter All ContentAll JournalsThresholds Search Advanced Search This content is only available as a PDF. © 2020 Andrew Scheinman2020Andrew Scheinman Article PDF first page preview Close Modal You do not currently have access to this content.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.429 | 0.156 |
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".