The politicization of education policies: The case of Ghana’s Free Senior High School Policy
Bibliographic record
Abstract
While many scholars recognize and criticize the politicization of education policies, scholarly attention to the strategies politicians utilize to politicize educational policy discourses remains limited. Focusing on the officials of Ghana’s two major political parties, the New Patriotic Party (NPP) and the National Democratic Congress (NDC), as policy actors, this paper investigates how officials of these two parties operationalized discussions regarding Ghana’s Free Senior High School Policy (FSHSP) to garner support for their parties while stoking resentment for their political opponents. The study employs a critical discourse analysis (CDA) framework and a dataset of 175 documents, including news stories, press releases, party manifestos, and government publications. The analysis reveals that both parties resorted to strategies of positive self-presentation and negative other presentation. The NPP contrasted its regime with the NDC’s tenure and framed the NDC as a threat to FSHSP and the education of the poor and vulnerable. The NDC problematized and highlighted implementation bottlenecks while framing the NPP and FSHSP as threats to quality education. I argue that through these strategies, NPP officials aimed to maintain incumbency while NDC officials advocated a regime change. The paper concludes by emphasizing the potential risks associated with politicizing education policies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".