Bibliographic record
Abstract
Abstract Since the inception of television, portrayal of crime and justice has been a central feature on television. In particular, the police are featured as prominent characters in many fictional crime programs. Some television cops, such as Joe Friday, Columbo, and Kojak transcend the genre and become enshrined within popular culture. Sometimes referred to as a police procedural, the police drama is a staple of both current and past television programming. In fact, almost 300 police dramas have aired on American network, cable, and syndicated television, with several new shows premiering each year. The vast majority of these shows are short-lived and are largely forgotten. However, some police dramas capture large viewing audiences and/or achieve critical acclaim. Sweeping changes within society have resulted in shifting portrayals of the police on television. Early portrayals focused on a law and order approach, in which the police were moral agents who represented a conservative, pro-establishment point of view. These types of shows represent the so-called “authentic” police drama. The authentic police drama features storylines and characters that engage in somewhat realistic investigative practices and depict relatively common criminal events. The classic example of an authentic police drama is Dragnet, while more recent versions would include shows such as the very popular Law and Order franchise. The 1970s represented the golden age of the police drama, with numerous shows that can be described as gimmicky, with police appearing as super-cops who could singlehandedly fight corruption and achieve justice. Moreover, demographic shifts in the field of policing led to more diversity in media depictions of police, with shows that featured female and African-American characters. In the 1980s, the portrayal of police became even more complex with the appearance of Hill Street Blues, a genre altering show that introduced serialized storylines and characters that were depicted with distinctly human characteristics, with real emotions and flaws. Moreover, the standard law and order approach was challenged, as a more liberal explanation of crime emerged with social inequality as a cause of criminal behavior. Contemporary police dramas, especially shows that appear on network television, tend to focus on a law and order approach. The emergence of cable networks has allowed the police drama to push the limits of television by depicting the police in a more realistic fashion.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.062 | 0.008 |
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".