Bibliographic record
Abstract
According the Youth Risk Behavior Survey (YRBS) conducted by the Centers for Disease Control and Prevention (CDC) among high school students, in 2003, 74.9 ([+ or -] 2.7) percent of the high school students had at least one drink of alcohol on one or more days during their life (CDC, 2004). Current alcohol use or high school students who had one or more drinks in the past 30 days was found be 44.9 ([+ or -] 2.4) percent (CDC, 2004). Percentage of high school students who had five or more drinks of alcohol in a row (binge drinking) on one or more of the past 30 days was 28.3 ([+ or -] 2.0) (CDC, 2004). With regard specific subpopulations of high school students also data is available. For example, in 2001, the Bureau of Indian Affairs (BIA) conducted the Youth Risk Behavior Survey (YRBS) among 8,511 students in grades 9-12 attending schools funded by BIA and found that 83% female students and 78% male students reported life time alcohol use (CDC, 2003). This group shows greater prevalence than the national data. It has been found that African Americans and Asian Americans are less likely misuse alcohol than whites and Hispanic Americans (Ellickson, McGuigan, Adams, Bell, & Hays, 1996). A survey was done about education in schools in 1996 that found that a median of 87.6% of the states and 75.8% of the cities included in the survey taught a separate education course in grades 6-12 and knowledge-based coverage about alcohol and other drugs ranged from 97-100% schools (Grunbaum, Kann, Williams, Kinchen, Collins, & Kolbe, 1998). While this appears quite impressive, is well known that the amount of time given for education in schools, and more so in high schools, is quite insufficient. There are several subjects that need be taught and education does not get enough attention. Furthermore, has been found that knowledge-based curricula are necessary but often insufficient for behavior change for a majority of students. Hence, there is a need for effective alcohol education programs in high schools. A cross-sectional survey was done with 1,236 high school students in Canada determine alcohol use beliefs and behaviors (Feldman, Harvey, Holowaty, & Short-t, 1999). In this study sample 24% of students reported never having tasted alcohol, 22% reported having tasted alcohol but did not currently drink, 39% were current moderate drinkers, 11% were current heavy drinkers (five or more drinks on one occasion at least once a month), and 5% did not answer the question. The most common reason given for not drinking was because was bad for health and due the upbringing they had received. The most common reasons given for drinking were cited as: enjoy it and to get in a party mood. Several specialized interventions have been implemented in high schools for primary prevention of alcohol use. Clearly there is a need for more alcohol education in high schools that is either dovetailed with existing education curricula or is in addition the existing education curricula. An Israeli intervention aimed at reducing abuse of alcohol among adolescents that was based on Botvin's social skills theory was implemented in seven high schools (Peleg, Neumann, Friger, Peleg, & Sperber, 2001). The results of the intervention showed that at one and two year follow-up the rates of alcohol consumption did not change in the intervention group (p > 0.05) but rose significantly in the control group (p Another component that has been found useful in high school interventions is peer support groups. It has been found that peer support groups are an economical and well-accepted method for early recognition and management of emotional and behavioral problems in high schools (Wassef, Mason, Collins, O'Boyle, & Ingham, 1996). …
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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".