A magyarországi állatorvostan-hallgatók pályaválasztásának motivációs tényezői 2016 és 2020 között = Motivation factors for the Hungarian veterinary students’ carrier choice between 2016 and 2020
Bibliographic record
Abstract
A szerzők kutatásának célja az volt, hogy felmérjék az állatorvostan-hallgatók pályaválasztásának motivációs tényezőit, így nagyobb eséllyel tudjuk feltölteni a szakterületi hiányokat is. A felmérés alapját képző kérdőívet a 2016 és 2020 között az Állatorvostudományi Egyetem állatorvos szakára, magyar nyelvű képzésre beiratkozó 548 hallgató töltötte ki. Az állatorvosdoktor szakot mindegyik hallgató első helyen jelölte meg, 73,9%-uk nő volt és a többségük kisebb városokból és Budapestről származott. A pályaválasztásnál a legtöbbet az elhelyezkedési esélyek, a szakma presztízse és a gyakorlatorientált képzések számítottak, de szintén fontos volt a hallgatói élet és az intézmény hírneve. | Background: Over the last few decades students’ expectations towards higher \neducation, including the veterinary studies, have changed significantly. Understanding students’ motivations is a prerequisite for adapting to these changes \nand helping them with career orientation, especially with the alarming shortages \nin certain veterinary fields. \nObjectives: The aim of our research was to survey the motivational factors of \nveterinary students' career choice. \nMaterials and Methods: The present study is based on a questionnaire which \nwas completed by 548 first-year students being enrolled into the Hungarian \nveterinary medicine course of the University of Veterinary Medicine Budapest \n(UVMB) between 2016 and 2020. \nResults and Discussion: All vet students applied for admission to UVMB as their \nfirst choice. The gender ratio did not change significantly over the surveyed years \nand 73.9% of the respondents were women. Most students started the university \nwithin 1-2 years after high school graduation, with an average age of 19.8 years, \nand came from Budapest and Pest County (altogether 41.8%). Vast majority of \nthe enrolled students was from different urban areas (33.8% from smaller towns, \n24.5% from Budapest and 20.8% from county seats) and only 20.8% came from \nrural circumstances. The most important motivational factors for veterinary education were job prospects, the prestige of profession and the practice-oriented \ncourses, but student life and the good reputation of UVMB were also important. \nThe motivational factors slightly differed between men and women. As regards \nto the information channels about the vet education and the admission process, \nalmost all vet students visited the governmental and university websites, and \nthey were mostly satisfied with their information content. The university publications, the UVMB Open Day and the educational exhibition were also preferred, \nbut less than half of the respondents visited the latter two. Communication via \nlandline telephone and high school career days were the least preferred ways of \ninformation collection.
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.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.038 | 0.004 |
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".