Map of the Land, Map of the Stars
Bibliographic record
Abstract
Before the highways, Yukon peoples freely travelled the rivers and trails, guided by the stars and their knowledge of the land. The play is about searching for our stories, gathering them, honouring them. It celebrates people’s deep connections between the land and the sky, which go back thousands of years for Yukon First Nations—the Indigenous people who lived here first. This play happens in many times and places. The audience time-travels back and forth with the seven performers to hear stories, songs, and dances from different times and people. This play explores how major events disrupted people’s way of life on the land. The Klondike Gold Rush was one. Thousands of stampeders came to the Yukon hoping to get rich. The building of the Alaska Highway during World War II brought more incredible changes to Yukon people. It also was very hard for the American soldiers who had to build it, many of them young African-American men. Some stories are about the colonization of Indigenous people: “the process where one group imposes its values and cultural beliefs on another group over time.” The laws, religions, and residential school system’s painful effects on families are part of these stories. The play also looks at how people come together in positive ways. Many fall in love with this land, and people already living here, and start new lives together. With this play, we’re trying to search for a good trail forward together, with reconciliation and harmony, for all of us.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.265 | 0.064 |
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".