Kapitalocæn didaktik:Om undervisning med fokus på klima, klasse og kapitalkritik
Bibliographic record
Abstract
Hvis man mener, at det er blandt skolens fornemste opgaver at klæde eleverne på til at træde ud i samfundet som livsduelige unge mennesker og aktive medborgere, må man på ethvert tidspunkt i historien spørge: Hvad er det for udfordringer, der tegner nutidens problemhorisont? Hvad er definerende for de kriser, vi nu og i fremtiden er tvunget til at forholde os til? Og hvilke store samfundsmæssige forandringer, står vi overfor som reaktion på disse kriser? Alle tre spørgsmål er afgørende, hvis man vil formulere konkrete bud på, hvilke former for undervisning, der fremmer livsduelighed og aktivt medborgerskab i kontekst af et samfund baseret på livsfjendtlige logikker og praksisser. De tre forhold, som jeg i dette kapitel har valgt at udpege som historisk presserende at forholde sig til, er klimakrisen, klassekampen og kapitalismen.
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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.025 | 0.011 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.112 | 0.045 |
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".