Convening Authority in Global Education: a Case Study of the OECD's Assessment of Higher Education Learning Outcomes
Bibliographic record
Abstract
How is authority convened in global education? In 2008, the Organization for Economic Co-operation and Development (OECD), an “elusive institution” that is nonetheless “routinely heralded as a leading organ of global governance” (Woodward, 2009: xiv), launched a cross-national, cross-cultural feasibility study that would reveal the contours of authority and legitimacy in global education governance. The Assessment of Higher Education Learning Outcomes (“AHELO”) feasibility study convened the world’s pre-eminent education experts along with education policy leaders in government and academia to assess whether it was technically and practically feasible to capture the value-added, or “learning gain,” associated with university education. The emergence of a field of academic study around the “global education policy field” (Lingard et al. 2007) coincides with important questions related to authority and legitimacy in global education governance. The study of global governance itself acknowledges that non-state (e.g., private, technical, epistemic) forms of authority not only help problematize, frame, and propose solutions to pressing public policy decision-making needs; non-state actors constitute key actors in the global governance architectures. My case study of AHELO offers an important empirical contribution to the nascent global education policy literature while enhancing our theoretical understanding of authority in structures of education governance spanning the OECD member states. Projects such as AHELO - often portrayed as expressions of a relentless force such as education neoliberalism, globalization, the audit society, or the dominance of wealthy states of the world - are in fact are quite tenuous constructions that rely on a challenging integration of legitimacy and stakeholders at transnational, national, and subnational levels. This dissertation offers compelling and original empirical insight into an innovative, historically-significant and yet politically unfeasible global education project. My dissertation presents global education governance as a “field” in which different actors compete for recognition of authority in the higher education policy space. In some OECD contexts, including the case studies presented in my dissertation, expert authority must compete with academic and university associations, governmental authorities, and even the authority of indicators like global university rankings. My case studies demonstrate how this field is contested in different political economies - shedding light on competition for authority in ways that are particular to variable political settings.
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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 | 0.028 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.012 | 0.015 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".