Bibliographic record
Abstract
For over 50 years, evaluators have used theories of change to articulate the causal logic underpinning how an intervention is intended to bring about a desired change. From its origins in programme evaluation, the approach has been adopted more widely for purposes from program design to program management. As theories of change continue to be used for multiple purposes, it is an opportune moment for the evaluation community—where the approach originated—to provide their perspective on the strengths and limitations of the approach and its future directions. To provide these perspectives, we asked nearly 30 of the world’s leading evaluators and programme theorists to provide a short essay on the past, present, and future of theories of change. This book presents their insights organized into five main themes: the use of theories of change in broader public policy contexts; using theories of change to establish causality; developing theories of change reflective of multiple stakeholder perspectives; using theories of change to understand wider societal change processes; and applying theories of change approaches for multiple purposes. By sharing these diverse perspectives, the book aims to both provide evaluators and emerging programme theorists with critical perspectives to inform future practice. <b>The Open Access version of this book, available at <a href="http://www.taylorfrancis.com">www.taylorfrancis.com</a>, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.</b>
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 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 | 0.005 | 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 | 0.000 | 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) | 0.013 | 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".