Re-Conceptualizing School Continuation & Re-Entry Policy for Young Mothers Living in an Urban Slum Context in Nairobi, Kenya: A Participatory Approach
Bibliographic record
Abstract
This article discusses the barriers to school continuation for pregnant girls and young mothers living in low-income and marginalized contexts in Nairobi, Kenya. In the article, I suggest adopting a girl-centered framework in the policy formulation process (Moletsane, Mitchell, & Lewin, 2015). This perspective puts girls’ voices at the center of the policy formulation process to help address the persistent gender inequality in education through problem identification and an exploration of ways to combat the challenges faced by girls. The article, which analyzes studies of government’s education policies, is supported by data from my recent fieldwork investigating young mothers’ challenges to school continuation and re-entry in Kenya, within the context of Kenya’s re-entry and continuation policy effected in 1994. I discuss the school re-entry and continuationpolicies in low-income contexts using the framework of critical feminism. I argue that there is need to integrate multi-pronged, participatory and feminist frameworks to promote systematic government educational policy reforms to shore up gender equality (King & Winthrop, 2015). To support this argument, I develop three main claims: (a) broad conceptualization of the causes of teenage pregnancy will promote the use of multi-pronged approaches to the design of school re-entry and continuation policies; (b) formulation and implementation of any robust policies on re-entry and continuation require strong integration of the voices, perspectives and the lived experiences of pregnant teenage girls and young mothers; and (c) the use of participatory visual methodologies will give voice to pregnant girls and young mothers, and promote policy dialogue while at the same time empowering them and spurring their agency to become part of policy formulation and implementation.
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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 | 0.023 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.018 | 0.022 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.004 |
| 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".