The African Storybook and Teacher Identity
Bibliographic record
Abstract
The African Storybook (ASb) is a digital initiative that promotes multilingual literacy for African children by providing openly licenced children’s stories in multiple African languages, as well as English, French, and Portuguese. One of the ASb pilot sites, a primary school in Uganda, served as the focal case in this research, while two other schools and libraries were also included. Data was collected from June to December 2014 in the form of field notes, classroom observations, interview transcripts, and questionnaires, which were coded using retroductive coding. Based on Darvin and Norton’s (2015) model of identity and investment, and drawing on the Douglas Fir Group’s (2016) framework for second language acquisition, this study investigates Ugandan primary school teachers’ investment in the ASb and how their identities change through the process of using the stories and technology provided by the ASb. The findings indicate that the use of stories expands the repertoire of teaching methods and topics, and that this use is influenced by teachers’ social capital as well as financial factors and policies. Through the ASb initiative and its stories, the teachers began to imagine themselves as writers and translators; change agents; multimodal, multiliterate educators; and digital educators, reframing what it means to be a reading teacher. Teachers’ shifts of identity were indexical of their enhanced social and cultural capital as they engaged with the ASb, notwithstanding ideological constraints associated with mother tongue usage, assessment practices, and teacher supervision. This exploration of teachers’ resourcefulness, needs, and realities provides a foundation for enhancing existing practices.
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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".