Bibliographic record
Abstract
Jorden er trådt ind i en ny geologisk tidsalder: den antropocæne. Mennesket er den dominerende livsform på planeten, og klimakrisen er en realitet. En realitet så omfattende og kompleks at vores eksisterende viden om naturkatastrofer ikke rækker. Med de udfordringer verden står overfor, er det nødvendigt at se på, hvad der binder os sammen, og hvordan vi kan styrke de tråde, der løber mellem alt levende — den intime, fundamentale forbindelse mellem mennesker og natur, som vi har glemt i dag. Bogen er en referenceramme og en ufuldstændig encyklopædi. En ufuldstændighed der afspejler verdens opbrudte, sammensatte tilstand. Det er ikke muligt at tegne et præcist, fuldkomment billede af en planet under forandring, og det rækker ikke at isolere problemerne eller at betragte det antropocæne fra et begrænset perspektiv eller fagområde. Bogen forsøger at fange de vigtigste positioner i den omskiftelige debat omkring planetens tilstand, samlet under spørgsmålet: Hvordan lever vi sammen? Og hvem er vi, når vi ikke blot er mennesker, men også natur? Denne engelsksprogede antologi rummer bidrag af knap 100 danske og internationale forfattere, forskere, filosoffer, kunstnere og arkitekter, heriblandt Bruno Latour, Donna Haraway, Peter Weibel, Greta Thunberg, Björk, Connie Hedegaard, Minik Rosing, Carsten Jensen, Josefine Klougart, SUPERFLEX og Tomás Saraceno.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.276 | 0.108 |
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".