Agricultural Experiences and Factors of Undergraduates Who Enroll in a College of Agriculture
Bibliographic record
Abstract
Industry partners and College of Agriculture, Food and Environmental Sciences (CAFES) faculty have observed students entering the college possessed fewer agriculture experiences and skills than their predecessors. They have also lamented the increasing pressure to develop industry-ready students, when the gaps are ever wider between their experience and skills entering college and what are required upon graduation. During the 2011 spring quarter, all CAFES students (N = 3,366) were sent an electronic survey that resulted in 911 responses (27% response rate). Three quarters of the students were female and one third were seniors. Prior to enrolling at the university, 34% had the opportunity to enroll in secondary agriculture courses but only 25% actually did enroll. Of those who enrolled in secondary agriculture courses, 15% enrolled all four years of high school. Only 28% were raised in a rural setting, with 12% on a farm and 12% on a ranch. When asked to identify what or who influenced their decisions to enroll in a CAFES major, the leading factor was parent(s), followed by a campus visit. Despite CAFES' large enrollment, former FFA and 4-H members are a minority, even with the work these organizations do to prime students for careers in agriculture. Recommendations to increase enrollment of students with agricultural experiences and skills include: encouraging students to attend campus events early in their secondary careers to capture interest and foster relationships, charging university faculty to attend local meetings and visit programs on their travels and crediting experiences and skills gained through organizations such as FFA and 4-H on admission metrics to ensure students entering CAFES have valuable experiences and skills to build upon.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".