Bibliographic record
Abstract
The concept of complexity is a popular and contentious topic. Just what is complexity? What does it mean to 'think complexly'? This paper addresses both of these issues. Complexity thinking is impossible to define with any precision as it deals not only with change, dynamic change, evergoing, but with transformative change. Definitions require stability, the very element complexity neither has nor aspires to have. Instead complexity asks us to see, to deal with a world in continual flux; but a world that does have patterns to it, patterns that bind and structure through their interplay. In short, complexity seeing/thinking asks us to envision our world and events within that world in terms, not of 'things' but of process. In so doing, we are moving from a science that studies particles to the new sciences of chaos and complexity that study the interactive relations between and among particles, events, happenings. After distinguishing the similarities and contrasts between chaos and complexity, and showing the characteristics of each, along with looking at systems closed and open, frames modern and post-modern, this paper enumerates practical aspects of thinking complexly: accepting ambiguity, allowing humility to permeate one's being, and seeking out and utilizing difference and diversity. The health care profession by its very nature of dealing with that which is dynamically living deals with the complex daily. Its routines and rules, though, are too often caught in a modernist trap. This paper challenges all health care professionals to break free from that trap, and suggests ways to do so.
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 | 0.020 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.024 | 0.087 |
| Scholarly communication | 0.018 | 0.013 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.010 | 0.012 |
| Insufficient payload (model declined to judge) | 0.008 | 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".