Bibliographic record
Abstract
This book analyses the attempts of the British Broadcasting Corporation (BBC) to use broadcasting as a tool of empire. From an early stage the corporation sought to unite home listeners with their counterparts in the wider British world, particularly in the British settler diaspora in Canada, Australia, New Zealand, and South Africa. The BBC saw this as part of its public-service mandate, and also as a means to strengthen its position at home: by broadcasting to and about the empire, it built up its own broadcasting empire. The BBC encouraged overseas the spread of the British approach to broadcasting, in preference to the American commercial model. During the 1930s it tried to work with the public broadcasting authorities that were established in the ‘dominions’: initially, these efforts met with limited success, but more progress was made in the later 1930s. High culture, royal ceremonies, sport, and even comedy were used to project Britishness, particularly on the BBC Empire Service, the predecessor of today's World Service. Commonwealth broadcasting collaboration intensified during the Second World War, and reached its climax during the late 1940s and 1950s. Belatedly, at this stage the BBC also began to consider the role of broadcasting in Africa and Asia, as a means to encourage ‘development’ and to combat resistance to continued colonial rule. However, during the 1960s, as decolonization entered its final, accelerated phase, the BBC staged its own imperial retreat.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.058 | 0.017 |
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".