Bibliographic record
Abstract
The landscape of North America is beautiful, pristine and wonderful.The land has majestic mountains such as the Rocky Mountains and the Great Smoky Mountains, and freshwater lakes such as the Great Lakes of North America and Lake Tahoe.North America is surrounded by the world's two largest oceans, the Pacific and the Atlantic.The vast continent is covered by deserts, forests, prairies, meadows, forests, canyons and wilderness.It has countless small towns as well as highly populated metropolitan cities.The land was first inhabited by Native Americans and First Nations, who lived off the land and in harmony with creation.It is a magnificent land, composed of only five countries, Canada, the USA, Saint Pierre and Miquelon, Greenland and Bermuda.Just as the land is diverse and bountiful, so are the people who live in these five countries.Though their history is short compared with countries in such contexts as Asia, South America, Africa and Europe, it has been filled by devastation, horror and suffering.With the European conquest of Native land, the terror began for many Native and First Nations peoples as genocide was committed against them.The large-scale enslavement and importation of Africans brought further injustice, horror and suffering.During this horrific history, Christianity had a large presence and was part of the very fabric that caused the genocide of Native Americans and the enslavement of Africans.Christian adoption of the Doctrine of Discovery and the perception of Africans as heathens made it theoretically justifiable to enslave them.In addition, Asians were viewed as heathens and foreigners, a perception which white Americans used to indenture them.Throughout this history of immigration, enslavement and conquest, Christianity was deeply implicated in colonialism, subjugation and domination.Due to increased immigration and the entrance of refugees during the last 70 years, North America is a very racially diverse place.This diversity means that various languages are spoken and different cultural customs are lived out.Many people who came from difficult situations found opportunities to build a new life in North America.Some refugees were able to start fresh lives and contribute to the wider society.Coming from many different backgrounds, they have formed an enterprising people who have built one of the world's strongest economies.North America has had the Civil Rights movement and recently the Black Lives Matter movement
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.650 | 0.444 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".