Influence of Socioeconomic Status and Gender on High School Seniors' Use of Computers at Home and at School
Bibliographic record
Abstract
This article critically assesses the proposition that computers have a democratizing effect in schools by increasing job-relevant skills among diverse groups of students. Drawing on arguments that schools are limited in their ability to counter long-standing patterns of inequality, we examine how gender and socioeconomic status interact to shape computer use patterns among high school seniors both at home and at school. Our data come from a large representative sample of grade 12 students in a western Canadian province. We find that social inequalities are being reproduced in the home through access to, and use of, home computers, with job-relevant uses higher among both female and male students from more advantaged backgrounds. Home environment conditions the effect of school use of computers because students from higher SES families—who have higher academic achievement and goals—are more likely to use computers at home but less likely to do so in school. This finding challenges claims that computers in schools can level differences in cultural capital that students acquire at home.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".