Storylines in public news media about mathematics education and minoritized students
Bibliographic record
Abstract
Abstract Public media both reflects and shapes societal perceptions and attitudes. Teachers and others around students in mathematics classrooms have expectations for the students, projected with what appears in these media. We are most concerned about the expectations placed on students who are identified with minoritized groups—particularly students who are Indigenous or migrated to Norway. We investigate how minoritized group contexts and mathematics education appear together in Norwegian news media texts. Our analysis uses the notion of storylines to describe the expectations about minoritized groups that news media project. We found seven entangled storylines: “the majority language and culture are keys to learning and knowing mathematics,” “mathematics is language- and culture-neutral,” “minoritized groups’ mathematics achievements are linked to culture and gender,” “extraordinary measures are needed to teach students from minoritized groups mathematics,” “students from minoritized groups underachieve,” “students from minoritized groups put in extraordinary effort and time to learn mathematics,” and “minoritized mathematics students are motivated by gratitude.”
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".