Making Development Marketable: The Politics of Image and Representation within Consumer Driven Schemes of Development Fundraising
Bibliographic record
Abstract
This project examines a new and growing form of international development fundraising, which constructs and packages development as a product of consumption in order to achieve its goals of awareness and fundraising. These efforts involve the use of a new set of marketing tools, technologies, languages, and tactics to encourage the sale of the development cause. The commodification of development activities within fundraising efforts ultimately poses an important quandary in terms of the effects that such ventures have upon public engagement and reception of international development. As such, this thesis explores the implications of such efforts for social justice in terms of the ways in which people’s perceptions of their own involvement and the causes of which they are a part are shifted. In order to more closely analyze such activities, the organizations (RED) and Kiva were chosen to act as case studies of both corporate and non-for-profit endeavours.
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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 | 0.013 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.058 |
| Scholarly communication | 0.017 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".