Bibliographic record
Abstract
The quarter’s Mountain Monitor finds that the pace of economic recovery in the Mountain West region’s major metropolitan areas converged toward that of the rest of the nation in the last quarter of 2013.\nWhile quarterly performance on the Monitor’s four indicators of economic recovery—employment, output, the unemployment rate, and house prices—varied considerably across the 10 major metro areas of the region, their combined performance broadly slowed to track with the rate of national economic recovery. The quarter’s average job growth remained unchanged in the region at 0.4 percent as the national economy caught up. The gap between the national unemployment rate and the average unemployment rate in the region narrowed to only 0.3 percentage points. Output growth slowed both in the Mountain West and nationally. And the pace of the Mountain West housing recovery slackened somewhat even as house price appreciation accelerated nationally.\nPerformance naturally varied by metro area, however. Tucson finally saw the value of its output exceed pre-recession levels as neighboring Phoenix closed 2013 on the cusp of reaching the same milestone. Albuquerque’s feeble recovery stalled again in the fourth quarter. Continued recovery on all indicators has left Boise looking less and less like the Sun Belt housing bust case study it resembled immediately after the recession and increasingly like peers in Colorado and Utah. Denver and Colorado Springs both saw unemployment decline solidly but otherwise their performance diverged. For their part, Utah’s three major metro areas continued to perform robustly on most metrics.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.437 | 0.252 |
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".