Alea iacta est. The legacy of Ancient Culture in Metal Music - A Probe into the Anglo-Saxon and Czech Production
Bibliographic record
Abstract
The bachelor thesis analyses the inspiration of antiquity in the lyrics of songs included in the genre of metal music. I begin by defining what metal music is, and then divide the analysis according to historical and mythological figures and themes associated with the period of antiquity. Thus, the thesis analyses the songs of metal authors inspired by the ancient environment and assesses their content in terms of the plausibility of the realities and mythology. I follow Czech and Anglo-Saxon metal music in comparison and examine how they respond to and reflect antiquity. Czech metal was chosen because it is not treated in connection with antiquity at all. Moreover, it represents work of a more regional scope. On the other hand, I have chosen Anglo-Saxon metal (UK, USA, Canada with regard to its global scope) as a corrective - an example of production of global significance. At the same time, however, I necessarily work with the material of Anglo-Saxon metal music selectively, without claiming completeness, given the possible scope of this work. I am mainly analysing the lyrics of the songs, so this is not a musicological point of view. The aim of this thesis is to synthetically evaluate the ancient references in metal music, to show the second life of antiquity in this cultural milieu, and...
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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".