Dunkel pædagogik i tværfagligt samspil:om sanser og følelser i klima-, miljø- og bæredygtighedsundervisningen
Bibliographic record
Abstract
For grundskolelærere kan elevfølelser ofte opleves som et besværligt og udfordrende element<br/>i undervisningen. Mange lærere oplever desuden ikke at have de fornødne lærerfaglige og relationelle<br/>kompetencer til at gå ind i elevernes følelser sammen med dem på fagligt meningsfulde måder. Denne<br/>artikel argumenterer imidlertid for, at der er store pædagogiske potentialer i netop at arbejde intentionelt<br/>og målrettet med sanselig-følelsesmæssigt aktiverende undervisning – ikke mindst når det<br/>kommer til at sikre kvaliteten af klima-, miljø- og bæredygtighedsundervisning. Artiklen gennemgår<br/>et håndgribeligt case-eksempel på dunkel pædagogik i tværfaglig kontekst for at illustrere denne<br/>overordnede didaktiske pointe.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.038 | 0.015 |
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".