Aligning Governance, Brand Governance, and Social Media Strategies for Improved Performance: A Qualitative Comparative Analysis (QCA) of Canadian National Sport Organizations (NSOs)
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
This paper explored the potential configurations of governance, brand governance, and social media strategies leading to effective organizational performance. A fuzzy-set Qualitative Comparative Analysis including 28 Canadian national sport organizations (NSOs) and six conditions highlighted two sufficient configurations for effective performance, defined as either budget per capita or athlete numbers. Although no single component of governance, brand governance, or social media strategy is necessary to succeed overall, brand reputation and the strategic use of social media to communicate NSO identity were common to both identified configurations. Accountability was important for effective performance in terms of budget per capita, while transparency was more important for higher athlete numbers. Thus, condition specificity is paramount in non-profit organizations that often have multiple objectives. Our study provides substantial theoretical and managerial implications, including the need to integrate brand governance and social media in non-profit organizations’ overall governance activities.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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