Organizational Development Level Determination Scale: A Validity and Reliability Study
Bibliographic record
Abstract
The aim of this study was to develop a scaling instrument for measuring organizational development level in the Turkish higher education context depending on perceptions of the faculty. The sample consisted of academicians of higher education institutions in the 2020-2021 academic year. Data were gathered in two stages. Exploratory Factor Analysis (EFA) was conducted in the first stage and Confirmatory Factor Analysis (CFA) was conducted in the second stage. The EFA sample consisted of 216 academicians working in 6 higher education institutions while the CFA sample consisted of 501 academicians working in 6 higher education institutions. Maximum Likelihood extraction and Varimax rotation methods were used in EFA. Results of EFA showed that the scale had a four-factor structure with 21 Items. The four-factor structure was confirmed with CFA. Cronbach’s alpha, Spearman Brown, and Guttman (G) were calculated in order to determine the reliability of the scores obtained from the scale. Item discrimination was verified by calculating Item-total correlation and item-remainder correlation. Also, t-test was carried out between upper and lower 27% to check item discrimination. Analyses were conducted making use of IBM SPSS 22 Statistical Package for the Social Sciences and AMOS Analysis of Moment Structure programmes. Overall, the results showed that the structure of the Organizational Development Level Determination Scale was valid. The measurement tool was concluded to have three factors and 18 Items, all in affirmative form.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".