Kras2011 : izkušenjsko učenje kot ključ za razširjanje znanja o vrednotah kamna
Bibliographic record
Abstract
Projekt KRAS2o11 je prvic prinesel kamnito vernakularno arhitekturo kot vsebino, ki je del nase arhitekturne dediscine med izobraževalne dejavnosti za studente godpodinjstva in biologije Pedagoske fakultete UL. Dejavnosti so potekale v avtenticnem okolju v okviru predmeta kultura bivalnega okolja. Kljucni cilj je bil predstavitev arhitekture kot nosilke razlicnih družbeno kulturnih pomenov v vecplastnem zgodovinskem okolju in casu. Studenti so raziskovali povezave med arhitekturo kot okvir bivanja v specificnem prostoru in dejavnosti vsakodnevnega življenja, ki so tesno povezane z znacilnosti prostora. Da bi kulturno krajino ohranili v vsej njeni raznolikosti in prednostih, moramo poznati in razumeti vernakularno arhitekturo dolocenega podrocja in njene vrednosti v preteklem in sodobnem casu. Pred izvedbo projekta smo izdelali nacrt dela, ki je vseboval nekaj didakticno metodoloskih iztocnic povezanih z izkusenjskim ucenjem. Sledili smo shemi opazovanje, doživljanje, reflesija in preskusanje konceptov v dolocenih razmerah. S podoživljanjem in interpretiranjem izkusnje prostora z domacin materialom - kamen, smo studentom, bodocim ucitelejm, skusali odpreti pot do kriticnega razmisljanja o odgovornem ravnanju z zgrajenim in naravnim okoljem.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.014 | 0.003 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.061 | 0.028 |
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".