Bibliographic record
Abstract
Effective coordination and communication are essential to the success of software organizations, but their study to date has been impaired by theoretical confusion and fragmentation. I articulate a theory that argues that the members of software organizations face a constant struggle to share and negotiate an understanding of their goals, plans, status, and context. This struggle lies at the heart of their coordination and communication problems. The theory proposes an analysis of organizational strategies based on four attributes of interaction that foster the development of shared understanding: synchrony, proximity, proportionality, and maturity. Organizations that have values, structures, and practices which facilitate these qualities find it easier to coordinate and communicate effectively. This argument has serious implications for traditional concepts in our literature. Project lifecycle processes and documentation are poor substitutes for informal but un-scalable coordination and communication mechanisms. Practices and tools are valuable to the extent that they enable the development of shared understanding across our criteria. Co-location and group cohesion take advantage of the four criteria and therefore have direct advantages for software teams. Finally, growth is detrimental to the effectiveness of the organization because it hinders the use of small-scale mechanisms and it leads to an undesirable formalization. The theory is supported with empirical evidence collected from five case studies of a wide variety of software organizations, and it has explanatory and predictive power. The thesis links this theory to other current research efforts and shows that it complements and enhances them by providing a more solid theoretical foundation and by reclaiming the relevance of synchronous, proximate, proportionate, and mature interactions in software organizations.
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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.024 |
| Scholarly communication | 0.009 | 0.029 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 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".