Kajian Supply Chain Management : Analisis Relationship Marketing antara Peternakan Pamulihan Farm dengan Pelanggan dan Pemasoknya
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study examined how schools prioritize ten key health concerns among their student populations over time and whether schools' prioritization of alcohol and other drug use (AODU) corresponds to students' substance use behaviours and cannabis legalization as a major policy change. Data were collected from a sample of secondary schools in Ontario, Canada across four years (2015/16-2018/19 [N2015/16 = 65, N2016/17 = 68, N2017/18 = 61 and N2018/19 = 60]) as a part of the COMPASS study. School-level prevalence of cannabis and alcohol use between schools that did and did not prioritize student AODU as a health concern was examined. Ordinal mixed models examined whether student cannabis and alcohol use were associated with school prioritization of AODU. Chi-square tests examined changing health priorities among schools pre-post cannabis legalization. School priority ranking for AODU was mostly stable over time. While AODU was identified as an important health concern, most schools identified mental health as their first priority across the four years of the study. No significant changes to school AODU priorities were observed pre-post cannabis legalization nor was school prioritization of AODU associated with student cannabis and alcohol use behaviours. This study suggests that schools may benefit from guidance in identifying and addressing priority health concerns among their student population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it