It's about time: How to study intertemporal choice in systems design
Bibliographic record
Abstract
Decision making pervades software and systems engineering. Intertemporal decisions involve trade-offs among outcomes at different points in time. They play a central role in systems design, as recognised since the inception of the software engineering (SE) field. They are also crucial for the sustainability of design decisions. However, temporal decision making is not adequately understood in SE. The field of Judgement and Decision Making (JDM) offers important empirical findings and research methods that could be utilised. This article establishes a baseline for studying how software professionals handle intertemporal choices. It examines how temporal distance affects choices in an example scenario, explores in what areas of software development such decisions can be found, and examines how systems design decisions can be characterised and studied as intertemporal. We developed a method to study intertemporal choice in SE, based on an initial set of psychological theory grounded in JDM. We instantiated the method in a study to elicit responses to an intertemporal choice task followed by a Cognitive Task Analysis (CTA) interview. We found that study participants overall tended to discount future outcomes, but individual participants varied wildly in how they valued present vs. future outcomes. They indicated several locations in which intertemporal choices occur in everyday software development. Based on these findings, and by reconciling our initial theory with existing JDM theory and results, we further developed and refined our theory and study method into a framework for studying intertemporal decision making in SE. To obtain a basis for more sustainable software systems design decisions, SE research should adopt a more comprehensive, detailed, and empirically consistent way of understanding and studying intertemporal choices. We provide suggestions for how future research could achieve practical methods that address essential characteristics of real-life systems design decisions.
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 | 0.014 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.007 | 0.015 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".