Bibliographic record
Abstract
This chapter focuses on the Lux Project, an undergraduate research and digitisation project at the University of Winnipeg that works with the Hetherington Collection, a teaching collection of ancient Mediterranean artefacts. In this chapter, we examine the impacts a small-scale project can have in its own community as we describe how the Lux Project volunteers engage with local audiences beyond the university and work to raise the profile of ancient Mediterranean studies in Winnipeg. In considering how to reach local groups outside of the academy, this chapter also explores the ways that undergraduate students can contribute to public scholarship as researchers and as public scholars themselves, incorporating the perspectives of three long-time Lux Project volunteers, Kira Lang, Colton Van Gerwen, and Bourke Karras. Since student work with the collection has involved a broad array of tasks including identifying and dating objects, archival research, digital preservation, and data management, this chapter also discusses how students’ interests and educational goals present opportunities that shape the path of the project itself. In the conclusion, we reflect on the flexibility of small-scale projects and how to make the most of this attribute in adapting public scholarship to suit the needs of local communities.
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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 | 0.001 | 0.002 |
| 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 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.086 | 0.026 |
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".