Bibliographic record
Abstract
How do I learn how to rap?If you have a brain and a voice, you're almost there.Now we just need to connect them.(o.A.: Learn how to Rap Like a Pro: My Top 10 Tips) Meine Ausfhrungen beginnen mit einer Erinnerung: Es war in einer Winternacht in Montreal um das Jahr 1991, zu einer Zeit also, als HipHop gerade erst auf der Bildflche erschien, als kulturelle Randerscheinung des stdtischen Underground.Einige lokale HipHop-Acts standen auf dem Plan in einem kleinen Club -eine der wenigen Lokalitten, die mit einiger Regelmigkeit HipHop buchten.Der Raum war mit einer bunten Mischung von englisch-und franzsischsprachigen HipHop-Heads aus dem stdtischen Umkreis bevlkert: Jugendliche aus Jamaika und der englischsprachigen Karibik, aus Haiti und dem franzsischsprachigen Afrika, dazu gelegentlich ein weier Student aus Quebec oder einer anderen kanadischen Provinz.Die polyglotte Kultur der Stadt zeigte sich in ihrer ganzen Bandbreite, verschiedene Dialekte und lokaler Slang, creole, patois, joual und die HipHop-spezifischen grosprecherischen Tne wogten durcheinander
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 0.004 |
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; both teacher heads agree on what is shown here.
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".