All the World Loves a Lover: Monarchy, Mass Media and the 1934 Royal Wedding of Prince George and Princess Marina
Bibliographic record
Abstract
Abstract This essay examines the little-studied 1934 royal wedding of Prince George, Duke of Kent, the youngest surviving son of George V and the famously glamorous Princess Marina of Greece to argue that the British media projected this event on a scale, and in ways, never seen before. More than on any previous occasion it was a royal event driven by intimate publicity, and by a coterie of courtiers, clerics and newsmen who were committed to elevating a ‘family monarchy’ as the emotional centre-point of national life. I suggest that this celebration of royal domesticity engendered popular support for the House of Windsor in a period characterised by political turbulence at home and abroad. In this vein, I argue that social elites orchestrated royal family events as mass mediated nation-building exercises designed to create loyal subjects to the Crown, and that new technologies transformed how media audiences and royalty interacted with one another.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".