Bibliographic record
Abstract
The city of Thunder Bay is the hub of North Western Ontario.With a population of about 113,000 this community is the cultural and economic centre of a vast area of this province.Though relatively isolatedthe closest major cities, Winnipeg to the West and Minneapolis to the South, are more than four-hundred miles distant -Thunder Bay does not deprive its citizens of activities which enrich their lives.If one discounts the obligatory, aggrandizing descriptions that are usually found in promotional publications and popular histories, one can readily see that this city has, nonetheless, long shed its coarse frontier image.Thunder Bay has several libraries and museums, an art gallery, two theatre companies (one of which is of national note), several dance schools, a male choir of international repute, a symphony orchestra and a community auditorium that attracts well-known entertainers.The Italian people of Thunder Bay, like most other ethnocultural communities, have contributed significantly to the cultural development of the city though the recognition of their efforts has been perfunctory.'It may well be that acknowledgment of the cultural contribution of Italians has been slow in coming because none of their cultural agencies has achieved a degree of prominence that would warrant greater recognition?Indeed, enhancement of culture by Italians seems to have been achieved more through the efforts of individuals than by the collective design of the community.Ralph Colosimo, a musician and director, Frank Tucci, as a strong proponent of Italian culture, Rita Ubriaco, an authority on all aspects of Italian opera, Italo De Rocco, a talented artist, to name a few, are noteworthy for their accomplishments.Nevertheless, in the last three or four decades, the Italian community, despite its greater preoccupation with economic well-being, has devoted some of its energy and talent to cultural pursuits.The Italian people of Thunder Bay, now well established and well represented in all ire of civic life, make up approximately 8% of the population.Official records state that there are 7,910
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.020 | 0.011 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.000 |
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".