Bibliographic record
Abstract
Ovaj rad je rezultat proucavanja fonda Myron Goldsmith, koji se nalazi u arhivima CCA (Canadian Center for Architecture, Montreal). Ucenik Mies van der Rohe-a i Hilberseimera na IIT u Chicagu, i autor konstrukcije kuce Farnsworth, Myron Goldsmith, prije svoje dugogodisnje karijere kao associate biroa SOM, preživljava između 1953 i 1955 dvije važne godine u Rimu: u tom razdoblju prati predavanja Pier Luigi Nervija i radi sa razlicitim mladim talijanskim gradbenim inžinjerima. Arhivska otkrica prikazuju novu sliku Goldsmithove formacije, i omogucavaju konacno razumijevanje upletenosti americkog arhitekta i inžinjera u talijanski kontekst. Također korisna i radi prikaza statusa sto ga Italija iz petdesetih i sestdesetih uživa, u polju konstrukcijske arhitekture, kod međunarodne publike. Nervi predstavlja, zajedno s Miesom, glavnu referencu Goldsmithovih istraživanja u tim godinama, prvenstveno zbog fascinacije za izražajnost konstrukcije, gdje arhitektura, structural engineering i estetika, koegzistiraju u složenoj praksi umjetnosti građenja. Govorimo o istraživanju koji je u isto vrijeme formalno i teoretsko, i koje nalazi u radu Nervija, te u radu suvremenih arhitekata i inženjera u Italiji, jedan od najvisih trenutaka u poslijeratnoj Evropi, kako dobro Goldsmith potvrđuje u pismu u kojem traži produžetak svoje stipendije u Italiji: “My theoretical work can be better done in Italy, indeed in Rome itself, it seems to me, than anywhere else in the world.”
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 | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".