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
For many nonprofit organizations throughout the world, government funding is an important income source and the government a major partner for collaboration. Yet, the mode of government–nonprofit relations as well as the funding mechanisms have undergone remarkable changes over the last decades. In particular, grants were largely outplaced by contract payments, and newer impact-related arrangements have emerged, notably driven by the prevailing paradigm of public sector management at the time. While receiving government funding can be evaluated positively as it enables nonprofit organizations to fulfil their mission-related purpose, to increase legitimacy, enhance reputation or build capacity, it may also come along with undesirable implications. Among them are mission drift, loss of autonomy, an increase of accountability and negative consequences of chronic state underfunding. Depending on the mechanism used for public funding, i.e., direct grants or contract payments, the (un-)desired side effects may differ, as theoretical reflection and empirical evidence demonstrate. Nevertheless, one needs to consider side effects of different public and private funding sources before concluding whether one source of income outmatches the other.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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