An interview with Stephen Waddington, Partner and Chief Engagement Officer at Ketchum and Visiting Professor in Practice, Newcastle University, Past President of the Chartered Institute for Public Relations (UK)
Bibliographic record
Abstract
In May 2015, the Journal of Professional Communication’s senior associate editor, Dr. Terry Flynn, sat down with Stephen Waddington, Partner and Chief Engagement Officer with Ketchum and past-president of the Chartered Institute for Public Relations in the United Kingdom (UK) to discuss and reflect upon his perspectives on the future of the profession and the challenges that are on the horizon for practitioners and current students of the profession. Waddington discussed how his formative training as an engineer in the UK has helped him to create new systems and processes to better understand and manage the multifaceted challenges that organizations now face within the public arena. Together with a number of UK and European professionals, Waddington has lead a number of crowd-sourced publications and learning tools designed to future-proof the practice of public relations.©Journal of Professional Communication, all rights reserved.
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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 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.006 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.009 | 0.022 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".