Comparison on Global Mindset of International and National High School Students
Bibliographic record
Abstract
The role of Global Mindset for individual’s qualities which enable leaders to influence people and organizations from different cultures is evidently important for leadership effectiveness in diversity contexts. While leadership is considered as one of the key competences to predict organizational excellence, its developmental process can start from a young age. Therefore, it is important to develop Global Mindset for young people. However, studies on global mindset in educational context are rare to find in comparison to that in organizational context. Indonesian educational system has been enriched with schools which are characterized by globally oriented education system known as SPK (Collaborative Education Unit) since the last decade. The objective of this study is to compare global mindset level of high school students from international school (SPK) and national school (SPN-National Education Unit) in Greater Jakarta area. A global mindset scale was delivered to 132 students (N SPK = 59; SPN= 73). The independent sample t-test statistic was used and a significant difference of Global Mindset level between SPK and SPN students was found. The score of SPK Students is consistently higher than SPN students, both in general and dimensional levels. While presenting the Global Mindset profiles of both educational contexts, predetermining factors are discussed; in addition, recommendations about school curriculum and atmosphere to develop students’ Global Mindset are provided.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".