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Record W7132887642

Empowering Children Through a Global Education Reading Program

2019· dissertation· W7132887642 on OpenAlexaboutno aff
Jemille Lai-Yin Chu Morrison

Bibliographic record

VenueTSpace · 2019
Typedissertation
Language
FieldMedicine
TopicFemale Genital Mutilation/Cutting Issues
Canadian institutionsnot available
FundersOffice of International Science and Engineering
KeywordsCurriculumTransformative learningGlobal educationReading (process)Study abroadTanzaniaGovernment (linguistics)SolidarityMulticulturalismGrassroots
DOInot available

Abstract

fetched live from OpenAlex

This 19-year global education curriculum project was conducted by a Canadian researcher in solidarity with a Tanzanian women’s rights activist who requested assistance with her campaign to end the continued illegal practice of female circumcision in her village. Years of fundraising, researching and planning resulted in filling a primary school with multicultural children’s literature to be used in a daily global reading program from grades one to seven. During the seven years of teacher training and curriculum implementation workshops in Tanzania involving global education and holistic education principles, the teachers expressed their shock over the unprecedented openness and critical thinking of their students. The students developed a keen awareness of social justice issues through their daily reading and book talks. By the upper grades, the male and female students articulated their stance against female circumcision without controversy, as though it was common knowledge that this was an illegal and unacceptable practice. Additionally, the students scored top results on their graduating national exams. The intent of the project was not to improve standardized testing results of the most disadvantaged, rural students and HIV orphans. This was a positive side-effect of the transformative powers of storytelling in the lives of children who are now better equipped to think critically about illegal, harmful cultural 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.414
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.002

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.

Opus teacher head0.019
GPT teacher head0.429
Teacher spread0.411 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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