PROSTITUTION JOHN HOWARD SOCIETY OF ALBERTA 2001 EXECUTIVE SUMMARY
Bibliographic record
Abstract
Prostitution is the exchange of sexual acts for payment. There are several factors that are associated with entry into the prostitution trade. Some of the more influential factors are age, early home leaving, childhood sexual abuse, drug abuse and a poor financial situation. Most prostitutes have encountered at least one of these problems, and many have experienced them in combination. The problems associated with street prostitution affect not only the prostitute, but also the community in which he or she works and the family members of the people using his or her services. Prostitutes often suffer physical and sexual abuse, drug addiction and low self esteem. Residential and commercial areas often experience traffic congestion, noise, litter, harassment of residents, declining property values and business loss. Families of those who procure the services of prostitutes can suffer financial hardship, distrust, emotional suffering and family breakdown. There are three legislative options that have emerged to address the problems associated with prostitution. The first option, further criminalization, proposes to strengthen prostitution related laws. The second option, decriminalization, proposes to remove prostitution related offences from the Criminal Code and replace them with municipal bylaws. The final option, legalization, maintains that prostitution is a social problem that should be legalized and regulated by the state.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.218 | 0.093 |
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".