An integrative methodology for creatively exploring decision choices
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
Purpose The authors translate their the concept of integrative thinking into a repeatable methodology, supported by a set of tools for thinking through difficult or “wicked“ problems, a process that offers a better chance of rejecting false choices and of finding a way through to an innovative alternative. Design/methodology/approach The authors divide their process into four phases. A case example illustrates each phase. Findings The four phases that make up the integrative thinking 10;process: articulating opposing ways to solve a vexing problem; analyzing those opposing models to truly understand them; attempting to resolve the antithetical approaches of the opposing models by creating new models that contain elements of the original alternatives but are superior to either one and testing the potential new solutions. Research limitations/implications Additional examples and detailed guidance is provided in the authors new book “Creating Great Choices: A Leader’s Guide to Integrative Thinking,” (Harvard Business School Press, 2017). Practical implications Several corporate examples of “wicked” problems to which integrative thinking might be applied are: After a merger, the combined sales organization is riven by dissension between proponents of two opposite approaches – one using direct sales and the other channel partners. The CEO of a retail bank struggling to manage the conflicting goals of increasing efficiency and improving customer service. Originality/value Applied thoughtfully, this new and tested methodology gives leaders at all levels a fighting chance at solving challenging problems and creating breakthrough choices.
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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| 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