Teaching self-reliance and empowerment in civics classrooms: Towards a sociopolitical capabilities approach
Bibliographic record
Abstract
This paper considers whether self-reliance and empowerment discourses within Nigerian civic education are sufficient to actualise civic education aims of promoting freedom, human agency, and active citizenship. Drawing on qualitative data, it analysed the representations of self-reliance and youth empowerment concepts in civic education curriculum and prescribed textbooks for secondary schools, along with six civics teachers’ understanding and classroom implementation of these concepts. Findings show that economic-centric/neoliberal perspective dominates the framing of these concepts within civic education. This dominant perspective is driven by how self-reliance is framed in Nigeria's education policy. Relying on human capability and sociopolitical development models, the paper argues that the neoliberal perspective framing of self-reliance and empowerment undermines actualising the goals of civic education: to empower citizens for civic agency and sociopolitical actions that challenge systemic issues, such as inequality and corruption, which perpetuate social injustices like unemployment and poverty targeted by economic empowerment. Noting an increase in poverty and unemployment targeted by human capital approaches, the paper recommends a shift towards sociopolitical capabilities-informed perspective on self-reliance and empowerment in civic education. This, it argues, will complement the economic-centric perspectives emphasised in vocational subjects and foster holistic human flourishing.
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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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.020 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| 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".