Seventy years of information systems development methodologies from early business computing to the Agile era: A two-part history Part 2: Later ISD to Early post ISD methodology era: Adapting to accelerated context expansion (1980–today)
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
Information systems design (ISD) methodologies emerged soon after business computers in the 1950s. They have been a central topic of research and professional discourse in the information systems (IS) field ever since. This is Part 2 of a two-part history of ISD methodologies from the pre-methodology era that laid the foundational thinking that has been incorporated into ISD methodologies until now. We apply a historical method to follow the narrative of ISD methodology evolution in a historical context to identify central innovations and milestones that changed the environment allowing new types of ISD outcomes and processes to emerge demanding novel methodological responses. We will study what changed, what stayed the same and where the major shifts occurred. Part 2 reports on the major innovations and milestones that changed the IS environment and lead to emergence of the Later ISD (1980–1990) and Early post ISD methodology era practices (1990–today) and associated methodological innovations and principles. In Part 1, we have reported on the Pre ISD (1880–1960) and the Early ISD methodology era (1960–1980) histories.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.001 | 0.001 |
| 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