Preparing Globally Competent Professionals and Leaders for Innovation and Sustainability
Bibliographic record
Abstract
The personal and organizational struggles and accomplishments revealed by the COVID-19 pandemic highlight that innovation is the defining trait of individuals and organizations that thrive in the 21st century. The global health crisis not only accelerated the global geopolitical tensions and disrupted organizations in all sectors, but confirmed the importance of preparing globally competent citizens, professionals, and learners who can effectively respond to the economic, environmental, and digital transformations in the 21st century through lifelong learning and professional development. Leaders today need to not only understand the financial, operational, sociocultural, and historical contexts of regional, national, and global systems, but also to build effective partnerships and trusting relationships with all stakeholders in effective policymaking, fostering an organizational culture that supports innovation and managing risks.\n\nPreparing Globally Competent Professionals and Leaders for Innovation and Sustainability is centered on international higher education’s role for the global common good. It critically examines the need for globally competent citizens, professionals, and leaders in the 21st century and higher education’s role in the global common good for a sustainable world. The book presents an evidence-based interdisciplinary framework and promising strategies to allow all learners to develop global citizenship and global leadership while addressing the need to prepare human capital for the global knowledge economy and digital transformation of the 21st century. Covering topics such as accessible education, international higher education, and organizational innovation, this premier reference source is an excellent resource for organizational leaders, executives, faculty and administration of higher education, government officials, human resource managers, industry professionals, researchers, academicians, and students.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".