Bibliographic record
Abstract
This work is part of a larger research project, started in 2004, on the soundscapes of the different forms of anthropization in Italy and Europe (cities, towns, villages, mountains, plains, sea, lakes, etc.), as an expression of the socio-economic and cultural changes produced by globalization. In this sense, the study of soundscapes is intended as a perspective of observation and analysis of the dominant models of socio-economic development, as they manifest and express themselves in everyday life. At the same time, the soundscape is a research laboratory where to explore new forms of "coexistence" and social development, in order to promote the well-being of individuals and the ecological, social and economic sustainability of development. This work represents a synthesis of the first three cities examined: Rome, Bologna and Prague. It deals with an experiential path of a subjective and emotional type, with no presumption of statistical representativeness, on the sound environments of the social contexts examined. For each of them, sound recordings were made, along a path of one or more days, subsequently reorganized into a short sound report of about 15 minutes each. For each of them an indication of the places where the sound recordings were made, the map of the recorded sounds and their classification, based on the referential aspects, according to the sound landscape analysis model developed by Murray Schafer over the years. seventy in Canada (1977) are reported. The audio files of the three sound reports made in the cities examined are also attached to the text.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.251 | 0.155 |
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".