“Follow the North Star: A Participatory Museum Experience,” Conner Prairie, Fishers, Ind.
Bibliographic record
Abstract
Inspired by a reenactment at a Young Men's Christian Association camp in Ohio in the mid-1990s, staff at the living history museum Conner Prairie, just north of Indianapolis, developed their own Underground Railroad program. Since 1998 more than ninety thousand people, many of them students, have taken part in “Follow the North Star.” For about ninety minutes, visitors become a group of fugitive slaves on the Underground Railroad in central Indiana in 1836, heading North to freedom in Canada. Created by Eli Lilly in 1934, Connor Prairie covers nearly one thousand wooded acres today and features attractions such as Indiana's oldest brick house, a Civil War Journey, and the Lenape Indian Camp. “Follow the North Star” is offered each year in April and November. Up to forty actors and staff are involved on a “200-acre stage.” In contrast to most of the other programs the museum offers, “Follow the North Star” requires visitors to be at least twelve years old. General visitors can take part in the evenings, while student groups participate in the daytime.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.025 | 0.008 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.023 | 0.002 |
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".