Bibliographic record
Abstract
Middle school learners in British Columbia are offered a variety of explorations or exploratory courses offered in modules. These modules fall under the Applied Skills, Design and Technology portion of the curriculum. Two of the modules suggested are Textiles and Food Studies, both of which fall under the home economics umbrella. The challenge I have found lies in how to connect and make sense of the 2016 BC Ministry of Education curriculum for Middle School Home Economics in a way that can be done in the short time frame allotted. My inquiry for this project lies in the pragmatic research paradigm. Through researching for years I have found few resources specifically tailored to middle school. As a result, I felt there was a gap that needed to be filled. In this graduating project have provided some insight and ideas for middle school HE teachers who need some assistance with what can be done realistically, within the constructs of the time frame and organization of the middle school exploratory model. Using a mixed methods approach I share my experiences, outline a day in the life of a middle school HE exploratory teacher and discuss the developmental characteristics of middle schoolers as well as middle school organization. I analyzed past and present curriculum for recommendations for teaching home economics in middle school. I created a website of resources for teachers who find themselves in this role. Finally, I reflect and conclude my experiences from my research.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.133 | 0.014 |
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".