Sea of Destruction: Legal and Social Forces Enabling Sexual Abuse of Children
Bibliographic record
Abstract
This Article seeks to expose the truth of how our schools, laws, and powerful groups in our society actively work to aid mobile molesters in schools—mobile because they move from child to child and school to school, all with the blessing of adult enablers who are charged to protect children. According to news reports, in 2015, at least 498 teachers and other school workers were arrested for sexual misconduct with children. That is almost three per school day. Even worse, in addition to the initial attack by the molester, the child is subsequently revictimized by others who aim attempt to protect the perpetrator and institution: bystanders, teachers, principals, special interest groups, government bureaucrats and politicians.\nThere are a body of laws and social forces that work to re-brutalize a survivor of child sexual assault. The decision to fail the vulnerable cannot be excused, must not be tolerated. That decision—perhaps decisions is a more accurate reflection—will be our primary focus. We do so to propose measures with one primary goal: to untangle the web of molesters-institutions-enabling that ensnares the vulnerable in a vice-like grip, with nowhere to run or hide.\nThis Article is comprised of three distinct, yet merged, voices: survivors from the US and Canada; data demonstrating the degree to which the mobility of molesters is institutionalized and enabled; recommendations for legislation focused on criminalizing the enabler. Our emphasis in this Article is specific: enablers protect teachers, coaches, and administrators who assault vulnerable school children mandated by state law to attend school. Focusing on the enablers holds them accountable for their actions and significantly curtails the ability of molesters to harm children. To protect these children, we propose creating mechanisms to criminalize enabling behavior. In that vein, our attention in this Article is not the molesters and their crimes but rather on those who created the infrastructure enabling the perpetrators. That does not minimize the actions of the molester but rather expands the focus to an additional, key actor in the crime.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".