Folkloras un Bībeles alūzijas Alberta Bela romānos "Saucēja balss" un "Cilvēki laivās"
Bibliographic record
Abstract
Maģistra darbā “Folkloras un Bībeles alūzijas Alberta Bela romānos “Saucēja balss” un “Cilvēki laivās”” pētītas alūzijas, pirmkārt, kā jēdziens, kas ieņem nozīmīgu lomu 20. gadsimta otrās puses latviešu literatūrā, un, otrkārt, kā organiska Alberta Bela prozas sastāvdaļa. 20. gadsimta otrajā pusē – 1970. un 1980. gados Latvijas padomju literatūra piedzīvo nozīmīgas pārmaiņas – aktualizējas patiess indivīda un laikmeta attiecību tēlojums, tomēr cenzūras un totalitārisma ideoloģijas dēļ par to nav iespējams runāt tieši. Maģistra darbā, izmantojot semantisko analīzi, tiek pētīts, kādu lomu folkloras un Bībeles alūzijas ieņem Alberta Bela romānos “Saucēja balss” (1973) un “Cilvēki laivās” (1987), nonākot pie secinājuma, ka tās abiem tekstiem piešķir mītisku un vispārfilozofisku dimensiju, ļaujot tos interpretēt plašākās cilvēka un laika attiecību kopsakarībās.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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".