Klassika kaasajastamise strateegiad Henrik Ibseni näidendite lavastustes Eesti nüüdisteatris
Bibliographic record
Abstract
Magistritöö käsitleb klassika kaasajastamist kolmes Eesti nüüdisteatri lavastuses, mis põhinevad Henrik Ibseni näidenditel. Analüüsitud lavastused on „Rahvavaenlane“ (2019), „Meister Solness“ (2022) ja „Nukumaja“ (2024). Uurimuse eesmärk on välja selgitada, milliseid strateegiaid klassikalise dramaturgia kaasajastamisel kasutatakse, kuidas aitab kaasajastamine tekitada seoseid tänapäevase ühiskonnaga ning millistes semiootilistes märgisüsteemides kaasajastamine ilmneb. Analüüs tugineb Gérard Genette’i tekstide muutmise strateegiatele, milleks on diegeetiline ja pragmaatiline ülekanne, transmotivatsioon ja transevalvatsioon. Magistritööst järeldub, et lavastustes avaldub kaasajastamine peamiselt visuaalsel, keelelisel ja näitlejatehnilisel tasandil. Kaasajastatud lavastustes võib lavastaja olla teadlikult võimendanud tänapäevaga suhestuvaid alustekstis esinevaid teemasid, näiteks naiste emantsipatsioon, lähisuhtevägivald ja meedia roll ühiskonnas.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.092 | 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".