Keep Your Options Open: Extreme Programming and the Economics of Flexibility
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
Financial evaluation and strategic analysis have long been considered two distinct approaches to evaluating new capital initiatives. An emerging valuation approach, known as real options, attempts to align finance and strategy through a new perspective: The value of an asset lies not only in the amount of direct revenues that it is expected to generate, but also in the options that it creates for flexible decision making in the future. In general, the more uncertain the future is, the higher the value of flexibility embedded in an asset, whether financial or real. This perspective has significant implications for the economics of flexible processes. Applied to software development, it could imply that a lightweight process that is well positioned to respond to change and future opportunities creates more value than a heavy-duty process that tends to freeze development decisions early. Thus, the feasibility of Extreme Programming (XP) can be supported by the option value of flexibility inherent in it. What is the theory that underlies this statement? How does it relate to the fundamental assumptions of XP? How does it impact the value of an XP project? What are the implications of such value propositions for project decisions? If you are curious, read on …
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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