Public Perceptions of International Development and Support for Aid in the UK: Results of a Qualitative Enquiry
Bibliographic record
Abstract
Summary Aid budgets face immense pressure – despite overseas aid being critical for poverty alleviation in developing countries and the explicit commitments of the world's industrialised countries to the Millennium Development Goals (MDGs). Public support for international development and aid will play a key role. Will the public become unsure about the UK's aid budget when they begin to feel cuts in government expenditure at home? How well equipped are we to ‘sell’ the UK's aid programme to a sceptical public in times of economic austerity? This working paper presents the results of a qualitative enquiry into public perceptions of international development and aid in the UK. Using data from the Mass Observation Project (MOP) at the University of Sussex, the authors investigate the views of 185 members of the general public. The study finds that, while people can conjure up ideas of why poverty exists, they know very little about the confluence of factors that actually drive poverty and/or the daily lives of the poor. Thus, poverty is seen as caused primarily by bad governments and natural disasters, almost as a stereotype. People have major doubts about the effectiveness of aid, perhaps reflecting the fact that they tend to be much better at picturing aid ‘failure’ than aid ‘success’. Nonetheless, there is support for aid in principle; people think that the UK has a responsibility to help the poor in developing countries, primarily on ethical grounds. This research has clear implications for the way in which the UK communicates with the British public about aid and development and the authors suggest a more considered approach that recognises the complexities of aid and is honest about what works and what doesn't. The paper concludes with a call for further research to fill the knowledge gaps that still exist about the drivers of public support for development and how those drivers can be influenced.
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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 | 0.021 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.012 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| 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".