Scrutiny on the Organizational Image Levels of the Students Studying at the School of Sports Sciences in Line with Some Variables
Bibliographic record
Abstract
The objective of this study is to scrutinize the organizational image levels of the students studying at the school of sports sciences in line with some variables. The subject group of the study consists of the prospective sportspeople studying in the 1st, 2nd, 3rd, and 4th years of the departments of Teacher Training on Physical Training and Sports, Recreation Training, Coaching Training, and Sports Management in the School of Sports Sciences at Selçuk University. The data collection tools used in the study are Organizational Image Scale and socio-demographic information form. In the assessment of the data, SPPS 25 (IBM Corp. Released 2017. IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY: IBM Corp.) statistics package program was used. The average ± standard deviation as well as percentage and frequency values of the variables were taken into account. The variables were assessed following the checks on the preconditions of normality and homogeneousness of the variances (Shapiro Wilk and Levene Test). In performing the analysis of the data, Independent 2 group t test (Student’s t test), Mann Whitney-U test when the preconditions were not met, One Way Variance Analysis for the three or more group comparisons; and Tukey HSD test, one of the multiple comparison tests; or, when it failed to fulfill the preconditions, the Kruskal Wallis and Bonferroni-Dunn test, also one of the multiple comparison tests; were used. The relation between two constant variables was evaluated via the Pearson Correlation Coefficient and in the cases that the parametric test preconditions were not met, via the Spearman Correlation Coefficient. For the significance level of the tests, the value of p < 0.05 and p < 0.01 was accepted. In view of the data obtained, it was determined that the organizational image levels of the participants were at a “moderate” level and that a statistically significant difference was present in the entertainment image as per genders; program and general appearance and physical infrastructure image as per their ages; quality, program, sports, general appearance, and physical infrastructure, social environment and accommodation-catering image as per grades; and in all image sub-topics when it comes to satisfaction with the university where they study. It is considered in conclusion of the study that the university can create a stronger corporate image through taking some factors like university’s general appearance, its physical infrastructure, personnel’s qualification, and enhancement of social environments, into account, for improving the organizational image levels of the university more and more.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".