Taxonomy for software teamwork measurement
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
ABSTRACT Despite the fact that software is mostly a team endeavor, the software engineering (SE) literature has not tapped into organizational psychology's conceptual and empirical writings on teams. This paper presents a model of team dynamics adapted to the specificities of SE project teams. The taxonomy is composed of nine episodes that are likely to be found in any software team process. Each episode is described in terms of the input‐process‐output cycle and illustrated with examples. The measurability of the episodes is validated on a capstone student project carried out with an industrial partner. The team activities are recorded by each developer, throughout the project's duration, in the form of work tokens. These work tokens are then associated with episodes by two independent coders. The results show that all the episodes of the proposed taxonomy are measurable, and very few (less than 5% in this field study) remain ambiguous. Most of the ambiguities arise from short episodes that alternate during team process activities. This paper's contribution to software team process research is to synthesize the team literature and draw up a theoretically driven taxonomy of team dynamics specific to SE teams and to provide initial evidence of measurability of the taxonomy. Copyright © 2014 John Wiley & Sons, Ltd.
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 | 0.002 |
| 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 | 0.001 |
| 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