Investigating top-down and bottom-up strategic alignment of event leveraging outcomes: the case of the 2021 UCI Road World Championships
Why this work is in the frame
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Bibliographic record
Abstract
Research question It is generally agreed upon that deliberate planning is needed to achieve pre-determined positive outcomes from sport events (i.e. event leveraging). There is less consensus around the specific strategies that should be used to achieve such outcomes, and ownership of such strategies. A largely conceptual suggestion has been made that both top-down and bottom-up stakeholders should be involved in event leveraging. Therefore, the purpose of this paper is to investigate the (mis)alignment of top-down and bottom-up stakeholders’ event leveraging objectives and how this (mis)alignment relates to objective achievement.Research methods In the context of the city of Leuven (Belgium), and the 2021 UCI Road World Championships, a case study methodology was employed with three phases of data collection and analysis of (1) top-down stakeholder documents; (2) semi-structured interviews with bottom-up stakeholders (n = 8); and (3) online questionnaires with residents (n = 3662).Results and findings We found alignment for only one top-down and bottom-up objective (i.e. promote cycling as a means of active transportation), which was found to be achieved through examining residents’ use of cycling for groceries. The remaining objectives were not aligned, and therefore were not fully met or sustained as indicated through resident opinion and behaviour.Implications The findings provide empirical support for previous conceptual notions that both top-down and bottom-up strategies to event leveraging are needed. Future research can help support leveraging sport events by working with both top-down and bottom-up stakeholders prior to hosting to help facilitate objective alignment, and foster relationships to maximize outcomes.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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