Conceptualizing the elements of research impact: towards semantic standards
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
Abstract Any effort to understand, evaluate, and improve the impact of research must begin with clear concepts and definitions. Currently, key terms to describe research results are used ambiguously, and the most common definitions for these terms are fundamentally flawed. This hinders research design, evaluation, learning, and accountability. Specifically, the terms outcome and impact are often defined and distinguished from one another using relative characteristics, such as the degree, directness, scale, or duration of change. It is proposed instead to define these terms by the kind of change rather than by the degree or temporal nature of change. Research contributions to a change process are modeled as a series of causally inter-related steps in a results chain or results web with three main kinds of results: (i) the direct products of research, referred to as outputs; (ii) changes in the agency and actions of system actors when they are informed/influenced by research outputs, referred to as outcomes; and (iii) tangible changes in the social, economic, environmental, or other physical condition, referred to as realized benefits. Complete definitions for these terms are provided, along with examples. This classification aims to help focus research evaluation appropriately and enhance appreciation of the multiple pathways and mechanisms by which scholarship contributes to change.
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 | 0.015 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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