Bibliographic record
Abstract
Muovendo dai nickname e dai luoghi che ospitano le centoventitré squadre delle quattro principali leghe professionistiche nordamericane (NBA, NFL, NHL, MLB), il volume offre una particolare narrazione geografi ca degli Stati Uniti e del Canada. Suddiviso secondo la tripartizione propria dei tradizionali studi regionali (ambiente, popolazione, economia), il testo propone però una chiave di lettura pop inconsueta. Le vicende e le passioni sportive, con il loro carico storico, sociale, economico e culturale, riflettono e sedimentano i caratteri del territorio. La dinamicità dello sport rivela un paesaggio iconico e incerto, quasi impossibile da fissare, eppure vero e reale. Le squadre blasonate, punti fermi che giocano nei “templi” noti a tutti gli appassionati, coesistono con le franchigie “variabili”, quelle suscettibili, modificate, dissolte, che non rimangono ferme e composte. Alcune giocano persino nello stesso impianto, ma la condivisione delle coordinate spaziali può condurre a luoghi diversi in tempi diversi: una geografia dinamica.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".