Social Media Platforms’ Use in Building Stakeholder Relationships: The Case of National Sport Organizations
Bibliographic record
Abstract
Social media has been widely touted by the popular media as an ideal tool to develop and sustain positive relationships between an organization and its stakeholders through the creation of dialogue. This research explores the validity of this claim via relationship marketing theory. The specific goal was to investigate how National Sport Organizations (NSOs) use their official Facebook and Twitter pages to create relationship dialogue with their stakeholders. A content analysis was conducted on the official Twitter and Facebook pages of 24 Canadian NSOs, and three hypotheses were tested. Results are contrary to the claims of those promoting social media, finding that Canadian NSOs’ Facebook and Twitter use did little to create a relationship dialogue. Results further note that NSOs preferred Facebook over Twitter.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.025 | 0.010 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".