The “Good” South African: Concepts of Nation-Building and Social Cohesion in the Public School Setting
Bibliographic record
Abstract
The purpose of this research project is to examine the ways in which the classroom, teacher, and student dynamics of a South African urban primary school create a site for nation-building, citizenship, and the promotion of social cohesion. Understanding that the school serves as an institution for the production of ideology, socialization, and spreading of knowledge, this research will investigate how curriculum, authority, and policy influence what it means to be a “good” South African citizen, and thus, a contributor to forming both personal and national identity. Through observing the “Life Orientation” courses, the research attempts to grasp the kind of civic engagement and/or skills that the government expects children to internalize at this young age. This research further explores the ways in which discipline is used in the classroom, and thus the ability of the learners to respond to these messages put forth by a higher authority—all of which is part and parcel of citizenship. Through messages from students and teachers, it is clear how the concept of the nation that is projected in the classroom is contested and confirmed, resisted and retained by members of the school community. Operating as its own democratic community, but under strict guidance and authority from government policy, this research paints a picture of how the school negotiates concepts of citizenship and nation-building in hopes of reaching state mandated goals of social cohesion. Through understanding the dynamics and conceptions cultivated within this public school, the following paper both adds to existing literature in the field of educational studies, political policy and development in post-conflict societies, as well as the field of social cohesion.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".