Humanity Is Ready to Flourish, Globally
Bibliographic record
Abstract
Abstract Approximately one quarter of people, globally, report that they are flourishing at work and in their lives overall. How might greater understanding and practice of Leadership for Flourishing bring along the remaining 75% of humanity and support flourishing more generally? The answer is connected to how leadership is evolving and how it is addressing the increasing complexity of Ecosystem-wide Flourishing (EWF) as whole-human well-being across multiple ecosystems: natural, social, organizational, and—for some—sacred. It is suggested the progress depends on fundamental change in how humanity answers three questions: who decides? (moving from a few to everyone), what do they decide? (moving from partial well-being to EWF), and how do they decide? (moving from indifference to love). If leadership has not focused on EWF, been inclusive, or guided by love, what steps can be taken to make the necessary changes? As many of the positive outliers found around the globe have shown, it is possible to lead for flourishing.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".