Written feedback and scoring of sixth-grade girls' and boys' narrative and persuasive writing
Bibliographic record
Abstract
This study examined the possible gender differences in teachers' scoring and written feedback on two narrative and two persuasive writing samples sent to 108 grade six teachers throughout one Canadian province. Participating teachers read a narrative and a persuasive piece of writing from one boy, and a narrative and persuasive piece written by one girl. The four papers were credited to a male author for some teachers and to a female author for others. The teachers evaluated the writing using the provincial scoring guides for narrative and persuasive writing. They also wrote comments and/or indicated needed edits and revisions on the piece of writing, providing the same kind of feedback to the student writers that they would provide to their own students. A two-way ANOVA was used to compare the scores by the teacher’s gender and the identified gender of the writer for each of the four papers. There were significant differences between scores assigned to female and male writers on particular papers within specific scoring categories. Nevertheless, teachers’ ratings of the writing showed no consistent patterns privileging female or male writers. Additionally, female and male teachers’ scores were not significantly different for three of the four writing samples. The persuasive papers overall were scored higher than the narrative papers. With one exception, the highest scores within each of the four scoring categories were assigned to papers whose writers were identified as boys. Teachers scored two papers higher when the student writer’s perceived gender matched their own (same-sex appreciation). Their scoring demonstrated the opposite effect (same-sex depreciation) for the other two papers.
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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 | 0.007 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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.
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".