Shaping the event portfolio management field: premises and integration
Bibliographic record
Abstract
Purpose This paper aims to examine how various academic disciplines shape the field of event portfolio management. Given the complex nature of portfolios comprising different genres that are studied separately from their respective disciplinary realms, the academic event portfolio landscape remains fragmented. This is against the nature of portfolios, which requires inter-disciplinarity and novel integration of genres, stakeholders and perspectives. Design/methodology/approach Based on a scoping literature review, this conceptual paper sets up a common ground for the academic study and industrial development of event portfolio management. Findings A comprehensive view of event portfolio literature across disciplines reveals its hypostasis as a compound transdisciplinary field. The authors suggest a set of foundational premises whereby they identify 22 principal thematic areas that comprise this emerging field. Practical implications The establishment of event portfolio management as a distinct field will help in the osmosis and diffusion of new ideas, models and best practices to run and leverage portfolios. The portfolio perspective highlights the need for cohesive learning to design comprehensive systems of events, implement joint strategies, solidify social networks, coordinate multiple stakeholders and develop methods of holistic evaluation. Originality/value By examining comprehensively event portfolio management as a transdisciplinary field, the authors have been able to identify principal research directions and priorities. This comprehensive analysis provides a synergistic ground, which at this embryonic stage of development, can be used to set out joint trajectories and reciprocal foci across the whole span of scholarship studying planned series of events.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| 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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".