Bibliographic record
Abstract
Because the American Ethnic Geography Specialty Group was established in 1992 and was, therefore, not a part of the original Geography in America anthology in 1989, we think it is beneficial to present briefly the development and context of American ethnic geography into which we can place more current work. In 2000 the American Ethnic Geography Specialty Group changed its name to the Ethnic Geography Specialty Group; but because almost the whole of this report deals with the decade of the 1990s, we use the specialty group’s original name throughout. American ethnic geography encompasses the geographic dimensions and experiences of ethnic groups in the United States and Canada. Its roots are in cultural-historical and population geography. As such, American ethnic geography reflects the epistemologies and methodologies of human geography. Like geographers in general, most American ethnic geographers are empirical and inductive in their research. Because ethnicity is a complex concept, scholars who research ethnicity have been troubled over the years by definitional conundrums. Although in his 1974 study Isajiw determined that most ethnic researchers never explicitly define the meaning of ethnicity, he examined twenty-seven characteristics of ethnicity to construct a definition of North American ethnicity as “an involuntary group of people who share the same culture or . . . descendants of such people who identify themselves and/or are identified by others as belonging to the same involuntary group” (ibid. 122). To Isajiw, then, a person is either born into an ethnic group and is therefore socialized as Anglo, Chinese, French, Polish, etc., or can decide at some point in her/his life which ethnic identity fits best, or other people can perceive a person’s ethnicity. As underscored in the Harvard Encyclopedia of American Ethnic Groups (1980), these latter internal/external modes of ethnic identification have become increasingly more significant in North America. Paradoxically, in today’s multiethnic American society, many ethnic groups are celebrating their heritages with renewed vigor, while, simultaneously, many people are less bound by past ethnic loyalties and have either used innovative terms of self-identification to describe their multiethnicity or simply refused to be categorized ethnically.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.074 | 0.022 |
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".