FRONTIERS OF E-BUSINESS RESEARCH 2005 Postmodern Knowledge Creation Approach in Software Product Development Companies Abstract
Bibliographic record
Abstract
This study applies the postmodern knowledge creation approach to the creation and development of knowledge in software product development companies and empirically tests the applicability of postmodern knowledge creation approach to software product design and development processes. The main characteristics of postmodern approach to knowledge creation are self-reflexivity in knowledge production, incredulity towards meta-narrative, capability of adaptation, and capability of being critical and suspicious of our own intellectual assumptions. It is hypnotized in this study that since the degrees of uncertainty and degree of change during software product design and development processes are relatively high, the characteristics of postmodern knowledge creation approach are applicable to the creation and development of knowledge in software product development companies. For testing the hypothesis, an empirical research is conducted on 52 small and medium-sized software product development companies in Canada. The findings of the empirical research support the main argument of this study and show that postmodern approach to knowledge is applicable to the creation and development of knowledge in most of surveyed software product development companies.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".