Bibliographic record
Abstract
This resource kit presents reasons for ensuring that sculpture becomes an integral part of British Columbia schools' art curriculum. An approach to creating readiness, a glossary, a criteria-based definition of sculpture, and a system of critical analysis is offered. The resource kit is complete with maps, slides, background information, classroom and fieldtrip activities. Its aim is to present, based on local resources, an integrated approach to the historical, critical, and productive domains of sculpture. An entire section of the thesis reviews, as a model for this approach, over one hundred and fifty pieces of sculpture found in Vancouver. Another section focuses on the technical aspects of producing sculpture. One media is developed as a model for each technique. Other media are listed with pertinent written and audio visual resources and examples of sculptors known for their work with these media. The appendix presents material to show the diversity of sculpture, both contemporary and historical, in local and international environments. The intention of the resource kit is to provide teachers with information concerning what sculpture can be, what sculpture is, and when, how, and why it is created. The hope is that this introduction and overview of this visual expression area will facilitate sculpture becoming an equitable part of British Columbia school art programs.
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 | 0.014 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.017 | 0.007 |
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".