Business Technology Management as Transdisciplinary IS-IT Competency Framework
Bibliographic record
Abstract
Digital transformation is accelerating and is increasing the demand for a new generation of leaders with hybrid skillsets, capable to manage IT but also co-create digital organizations. It requires professionals, trained in IS and IT disciplines, spanning business, computing, or engineering schools, to grow beyond their fragmented and competing specializations, and work together within a more integrated IS-IT profession. We report on a recent initiative, entitled Business Technology Management (BTM), and its ongoing applied research project, the development of a new BTM Body of Knowledge (BOK). Launched in Canada and supported by 22 colleges and universities, it aims at rebranding IS and IT programs, ensure collaboration between disciplines, and create more seamless career paths. Our paper offers an update on the BTM initiative and outlines the BTM BOK as an integrated transdisciplinary competency framework.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.003 | 0.016 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".