Integrated Literacies in a Rural Kenyan Girls’ Secondary School Journalism Club
Bibliographic record
Abstract
Our purpose in this paper is to foreground contextual issues in studies of situated writing practices. During a year-long case study in a rural Kenyan secondary school, we applied a number of ethnographic techniques to document how 32 girls (aged 14-18 years) used local cultural and digital resources (i.e., donated digital cameras, voice recorders, and laptops with connectivity)within the context of their after-school journalism club. We take inspiration broadly from the concept of liminal spaces, which we bring together with notions of placed resources, New Literacy Studies (NLS), multiliteracies, multimodality, and identity work. We argue that the learning space of the journalism club, including its mediating digital tools, affords identities of empowerment to students’ writing and experimentation. On close examination of the transitional space of the journalism club, we see the foundational practices of situated rehearsal, appropriation, and performance of the roles and linguistic repertoires that the learners associated with competent journalists. We conclude that the club as a learning space, including its “props” and digital resources, fostered new degrees of freedom, community, equality, and creativity. We are left with questions about the characteristics of transitional learning spaces and how these might serve as fertile ground for growing competent writers in a range of educational contexts.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".