Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
At the dawn of a new decade, I cannot help but recall that when I started my academic career in social work in the 1990s, it was common to look ahead to how life would be in the next century. Statistical projections forecast various demographic changes, often using 2020 as the future time frame. Back then, 2020 sounded far away and almost alien. Well folks, the future is here. Now that 2020 has dawned, it seems that the more things change, the more they stay the same. Certainly, the specific issues that social workers address have changed over the decades, and our approaches have been modified to tackle the new issues, but the struggle to understand and meet emerging needs persists. I used to jokingly hear that the ultimate goal of the social work profession was to put ourselves out of business. Given the intransigence of intolerance for difference and the persistent emergence of needs arising from “advances” of modern living, it seems the social justice stance of our profession will never be fully met. Indeed, our social contract is continually expanding. In the Fall 2019 issue of Advances in Social Work we are pleased to present 14 papers--11 empirical, 3 conceptual--written by 29 authors from 12 states across the U.S., representing different regions of the country and Ghana. Each paper is briefly introduced below.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 it