Bibliographic record
Abstract
The US Environmental Protection Agency (EPA), eager to make the best possible use of innovative programs, set up an Innovations Action Council (IAC) in the fall of 1996. The Council comprised all the senior managers of the agency from national and regional offices, gathered together once every quarter to focus on the EPA's use of innovative methods. The express purpose around which the Council gathered was framed this way: The IAC's goal is to develop an innovations strategy that deploys innovative approaches and tools that make measurable progress on important environmental problems . As a focal point for the IAC's discussions, this single sentence reflects both an appreciation of the need for innovative methods, and a conviction that innovation is not for its own sake but counts only when it makes a difference on problems that matter. Despite these positive ingredients, the sentence remains quite ambiguous about which of two quite different modes of organizational behavior it might produce. It can be read either forwards or backwards, and this simple choice significantly affects the operational consequences. Reading the sentence forwards, the agency would begin by listing the innovative approaches and tools in its repertoire. Then, with these tools in mind, managers would proceed to search for important environmental problems where those tools might offer measurable progress . The starting point for such deliberation, therefore, is an expanded toolkit filled with tools the agency has already learned how to use.
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 | 0.062 | 0.125 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.015 | 0.066 |
| Scholarly communication | 0.029 | 0.042 |
| Open science | 0.006 | 0.027 |
| Research integrity | 0.011 | 0.013 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".