Teacher policy reforms in the global South: Global, state and local intersections
Bibliographic record
Abstract
Globally teachers’ have witnessed intense reforms affecting their work (Day & Smethem, 2009; Fischman, 2000; Troman, 1996), at times with the close involvement of international organizations (Fischman, 2000). These processes raise particular implications in the global South. With often the attachment of aid as an incentive, and due to unequal equal power relations, the global influence on local education policies in global South countries becomes more powerful while the local politics more marginalized (Williams, 2015). Egypt is representative of global South countries that are subject to considerable global influences on the articulation of their educational policies. Teachers in Egypt have been subject to many reforms that echo global trends. The state claims to professionalize” teaching while simultaneously excluding the teachers from policymaking. Furthermore, there is a strong presence of international organizations in financing and directing many of those reforms. Meanwhile, teacher groups perceive in these reforms further marginalization and a loss of control over their work (Abou Zaid, 2013). I wonder how do these contradictory influences – of global and local dynamics –influence struggles over teachers’ work and their professionalization? To address these concerns, I examine controversies over teacher policy reforms in Egypt introduced during the 21st century.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".