Bibliographic record
Abstract
The back entrance of the Copenhagen Central Station has for some decades been shelter and meeting place for alcoholics, drug abusers and drug dealers, because this part of the Central Station faces a part of the town which for more than a hundred years has accommodated prostitution in general, and since the legalisation of selling pornographic films and pictures in 1969 also shops and cinemas for that purpose. When hash and narcotics entered the milieu of prostitution this part of town – called Istedgade kvarteret (Isted Street Quarter) – became also domicile of junkies, drug dealers and prostitutes dependent on narcotics. After a radical restoration of the Central Station in the 1990’s the management wanted to get rid of the abusers in the back entrance. So did many travellers. And as the police did not succeed they bought a music concept from the central station in Hamburg, which had proved its efficiency there. By playing music from the period of romanticism (about 1800-1860) from a loudspeaker they stressed the abusers so much that they after a few days of persistence left the entrance hall. Now the question is: what made them leave? – It is well known that music has been used for psychological purposes, in super markets, in films, in wars and as means of torture. But why should music from exactly that historical period affect the abusers? Most of the junkies and alcoholics are not familiar with nor attracted to classical romanticism. They have through their whole are anthropologists, who do not settle for surfaces, but insist on reflecting on their own incorporated cultural learning processes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.751 | 0.700 |
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".