COMMUNITIES AND LEADERS AT WORK IN THE NEW ECONOMY: A COMPARATIVE ANALYSIS OF AGENTS OF TRANSFORMATION IN
Bibliographic record
Abstract
Without change, stagnation is inevitable. Never has this truth been more obvious than during the current epoch of industrial decline in North America. This research provides two economic narratives that exemplify the struggles of industrial communities as they strive to regenerate. The research involves a comparative analysis of the transformation of two steel cities, Pittsburgh, Pennsylvania, and Hamilton, Ontario, from 1970 to 2008. For cities in which one major industry has formed the foundation of the local economy, job losses can result in massive dislocation and devastating consequences for individuals, families, and communities. Pittsburgh and Hamilton are among many cities striving to diversify and strengthen their economies as manufacturing diminishes and Western sunset industries rise in the East. Transformation has been much more extensive in Pittsburgh than in many cities because Pittsburgh was so largely dominated by the steel industry and faced a virtual collapse of that industry. Hamilton has also experienced a steep decline in steel and related manufacturing jobs. Based on 55 interviews with city leaders, including a pilot study in Welland, Ontario, this research examines eight critical factors that collectively influence development: transformational
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.012 | 0.012 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".