A Critical Discourse Analysis of the Resistance to the Implementation of Comprehensive Sexuality Education in Ghana
Bibliographic record
Abstract
The decision of the Ghana Education Service to introduce comprehensive sexuality education (CSE) into its pre-tertiary education curriculum received a barrage of attacks from politicians, religious leaders, and the Ghanaian media, prompting the government to perform a U-turn on its implementation. Drawing on a dataset of 120 articles comprising news reports, op-ed pieces, and editorials, I explore the discursive strategies employed in the Ghanaian media to resist CSE implementation. I combine insights from critical policy analysis and critical discourse analysis to shed light on how, through the media, individuals and groups other than curriculum experts influence educational policies. This study draws on existing theorization of policy as the authoritative allocation of values to argue that resistance to CSE stemmed from the discrepancy between the perceived values espoused by CSE and Ghanaian traditional heteronormativity. Resistance strategies utilized included sensational headlining, framing CSE as a covert means to expose/acclimate students to LGBTQI+ lifestyles, framing CSE as a danger to Ghanaian values, framing CSE as a foreign imposition, and threatening a regime change. The findings strengthen scholarly understandings of how education policies are resisted in public discourse and the need for a broader education policy formulation process that is culturally sensitive.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.030 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.012 | 0.022 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".