Crossroads & Connections: 2024 Tracking Oregon's Progress Report
Bibliographic record
Abstract
Oregon is at a crossroads. Communities across the state continue to grapple with social and economic strains while they also find opportunities to make progress on key measurements. The 2024 Tracking Oregon's Progress Report from Oregon Community Foundation provides data and analysis in seven focus areas that define what makes a thriving and healthy community. The 2024 Tracking Oregon's Progress report suggests that many systems and structures that shape the critical conditions for well-being are struggling and not working for Oregonians consistently. The cost of Oregonians' daily lives is increasing faster than their incomes and other sources of wealth. For example, the cost of childcare in Oregon takes up nearly a quarter of household income, on average, which rivals housing and college expenses. More than half of Oregonians reported feeling left behind economically. The report adds that the social divides facing Oregon communities leave residents feeling disconnected and socially isolated. Yet, the report also points to promising opportunities that can have positive impacts on community well-being. For example, investing in early childhood education produces an array of benefits that stretch well into adulthood. The report also points to investments in specific pressure points that can have a big impact, including building workforce and affordable housing and alleviating the cost of higher education.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.238 | 0.116 |
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".