Exploring the association between STEM-related family habitus and engineering identities of high school summer campers
Bibliographic record
Abstract
STEM (Science, Technology, Engineering, and Math) outreach activities are popular approaches to K-12 informal STEM learning which seek to address STEM education inequities. However, in Canada, there is limited literature exploring the combinations of barriers and privileges that impact youths’ access to informal STEM education. To understand youths’ affective engagement in STEM education, as impacted by factors of habitus and capital, constructs such as identity are being frequently explored, with pilot work done by our lab. Our pilot work suggests paid summer outreach camps affiliated with postsecondary institutions may draw in youth from families with ‘high’ socioeconomic status and STEM habitus. Additionally, youth tend to come into the camps with ‘high’ pre-existing engineering identity. These initial findings prompted us to explore the relation between youths’ engineering identities and their perceived family STEM habitus and capital. Through a survey of high school students in an outreach engineering camp we measured youth’s engineering identity and family STEM habitus and capital. Our results indicate a positive relationship between students’ perceived family STEM habitus and their engineering identity. Additionally, we found that students with higher family STEM capital showed higher engineering identity. This work offers valuable insight for outreach educators to understand the privilege perpetuated by strong family STEM environments and develop strategies to fill the resource gaps for students with lower STEM-related family habitus and capital.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".