FROM FRONTLINES TO BOARDROOMS: LESSONS IN LEADERSHIP AND INNOVATION FROM UNDER THE MANGO TREE
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The authors (Bartkus, Professor Emerita at the University of Notre Dame; and Block, the George M. Cormie Chair of Management in the Alberta School of Business) write about the applicability of lessons learned in war zones and other extreme environments for today’s business challenges. Dr. Bartkus “founded the Business on the Frontlines Program seeking to harness the dynamism of business in rebuilding societies ravaged by conflict and deep poverty.” Case studies are provided, “from the dusty roads of Uganda to the high‐stakes vaccine distribution efforts of J&J,” during the COVID‐19 pandemic. The authors contend that they “uncover a universal truth about leadership: the most powerful innovations often emerge from the most challenging environments. Whether facing armed middlemen or vaccine skepticism, leaders who can adapt frontline strategies to their unique contexts gain a critical edge in our increasingly complex and interconnected world.” The lessons include, in their words, Map the Entire Landscape and Follow the Money , Build Unconventional Partnerships , Fail fast and forward , and Get Your Boots Dirty . They believe that “effective leaders in challenging environments must look beyond traditional partners and stakeholders. This often means overlooking salient differences and digging deeper to understand the motivations and needs of all parties, including potential adversaries.”
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 it