Advocacy as Political Strategy: The Emergence of an âEducation for Allâ Campaign at ActionAid International and the Asia South Pacific Association for Basic and Adult Education
Bibliographic record
Abstract
This dissertation explores why and how political advocacy emerged as a dominant organizational strategy for NGOs in the international development education field. In order to answer this central question, I adopt a comparative case-study approach, examining the evolution of policy advocacy positions at two leading NGOs in the field: ActionAid International and the Asia South Pacific Association for Basic and Adult Education (ASPBAE). Although these organizations differ in significant ways, both place political advocacy at the centre of their mandates, and both have secured prominent positions in global educational governance. Through comparative analysis, I shed light on why these organizations have assumed leadership roles in a global advocacy movement.\nI focus on how the shift to policy advocacy reflects the internal environment of each organization as well as broader trends in the international development field. Ideas of structure and agency are thus central to my analysis. I test the applicability of two structural theories of social change: world polity theory and political opportunity theory; as well as two constructivist approaches: strategic issue framing and international norm dynamics. I offer some thoughts on establishing a more dynamic relationship between structure and agency, drawing on Fligstein and McAdam’s concept of strategic action fields. \nIn order to test the utility of these theoretical frameworks, the study begins with a historical account of how ActionAid and ASPBAE have shifted from service- and practice- oriented organizations into political advocates. These histories are woven into a broader story of normative change in the international development field. I then examine the development of a number of key advocacy strategies at each organization, tracing how decisions are made and implemented as well as how they are influenced by the broader environment. I find that while it is essential to understand how global trends and norms enable and constrain organizational strategy, the internal decision-making processes of each organization largely shape how strategies are crafted and implemented. These findings offer insight into the pursuit of advocacy as a political strategy and the role of NGOs in global social change.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.025 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.007 |
| 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".