Breaking into a free state of mind: Rationale and evidence for ‘study abroad’ out of rural South Africa
Bibliographic record
Abstract
This edited volume reveals how the journey of transformation at the University of the Free State (UFS) became interwoven with student leadership development and global learning. The UFS initiated two intersecting co-curricular programmes, namely, the First-Year Leadership for Change (F1L4C) programme in 2010; and the triennial Global Leadership Summit (GLS) in 2012. Although these programmes changed over time, their core focus remained to be the development of transformational student leaders through the creation of global learning spaces. From its inception in 2010 to the last GLS in 2018, the UFS global learning project involved 780 students and 259 staff members from 109 institutions, across four continents. The goal of this edited volume is to create a deeper understanding of how the UFS F1L4C and GLS programmes enhanced student leadership development through global learning, especially in the context of higher education transformation.
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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 | 0.011 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".