Bibliographic record
Abstract
Connecting seven essays written over three decades from 1979 to 2010 is the focused study of communication practices to optimize results – whether to teach oral communication, strengthen democracy, grow organizational trust, build community relations, or sustain fundraising. The book incorporates lessons from leaders in more than twenty high-performing organizations in the United States, United Kingdom, Canada, Australia, and New Zealand. Also distilled are understandings from ground-breaking study of the leaders of institutional advancement in some of the most successful universities in the world. The essays outline approaches individuals and organizations use to engage communication strategies, processes, and behaviors that accomplish exceptional results. Contents: 1. Developing Oral Communication. 2. Rhetoric of Democracy. 3. Developing the Culture of Trust. 4. Improving Community Service. 5. Benchmarking Advancement. 6. Beyond Benchmarking Advancement. 7. Sustain Funding Growth. References and Bibliography. Collecting papers shared at conferences or seminars of The Royal Society of Queensland, Corporate Communication International, The Council for Advancement and Support of Education, and in publications of the State University of New York Press. Keywords: communication, tertiary education, organizational development, fundraising, institutional advancement, oral communication, democracy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.115 | 0.043 |
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".