School communications 2.0: A social media strategy for K-12 principals and superintendents
Bibliographic record
Abstract
The purpose of this qualitative, multiple-case study was two-fold: 1) to describe, analyze, and interpret the experiences of school principals and superintendents who use multiple social media tools such as blogs, microblogs, social networking sites, podcasts, and online videos with stakeholders as part of their comprehensive communications practices, and 2) to examine why the principals and superintendents have chosen to communicate with their stakeholders through social media. Qualitative, semi-structured interviews with 12 principals and 12 superintendents purposefully selected from four regions of the United States and Canada were conducted. Social CRM served as the framework for the study. Findings revealed four themes that applied to both groups: 1) Social media tools allow for greater interactions between school administrators and their stakeholders; 2) Social media tools provide stronger connections to local stakeholders, to fellow educators, and to the world; 3) Social media use can have a significant impact on a school administrator's personal and professional growth; and 4) Social media use is an expectation; it's no longer optional. Implications for practice, for boards of education, for educational leadership programs, and for expanding the definition of Social CRM are included.
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.021 | 0.005 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".