Bibliographic record
Abstract
Abstract Milwaukee means “the good land” in Anishinaabemowin, the language group of the Indigenous people who have lived in the region since the 17th century. Milwaukee is nestled between a subcontinental divide and the western shoreline of Lake Michigan. Some 10,000 years ago, the retreating Wisconsin glacier shaped the region’s topography: at sea level and relatively flat near Lake Michigan and rolling hills in the Kettle Moraine area north and west of the city’s site. The Milwaukee, Kinnickinnic, and Menomonee rivers converge in the city. The water made the land fertile and defined its promise as a transportation hub. Milwaukee grew from this rich potential into the largest and most diverse city in Wisconsin. During the 19th century, it transformed from a collection of Indigenous villages with a Metis trading post into an industrial powerhouse specialized in heavy manufacturing and brewing. European immigrants (especially from Germany and Poland) and migrants from the eastern United States staffed Milwaukee’s businesses and settled the region with farming hamlets and suburban municipalities. By the early 20th century, Milwaukee consistently ranked among the top twenty US cities by population. But because the city’s area was so compact, it was also one of the most densely populated. For half of the 20th century, Socialists governed Milwaukee. Unusually among Midwestern cities, Milwaukee’s Socialists waged a campaign to annex surrounding areas, leading to a wave of defensive suburban incorporations after World War II. In the second half of the 20th century, the third wave of the Great Migration brought large numbers of African Americans to Milwaukee’s North Side, and Mexican Americans settled permanently on the South Side. At the same time, the city and its industrial suburbs began to shed manufacturing jobs and decreased the white population. Although the suburbs maintained separate governance, Milwaukee and its surrounding counties (Ozaukee, Washington, and Waukesha) grew into an interconnected metropolitan whole. In the 21st century, the city’s population stabilized at a bit under 600,000 residents, and local government spearheaded downtown revitalization efforts. Approximately one million people lived in the surrounding counties.
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 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.637 | 0.383 |
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".