Bibliographic record
Abstract
In this chapter I call for participatory monitoring and evaluation (M&E) of information and communication technology for development (ICT4D). I describe the ontology of ICT4D as complex and unpredictable. I favour an epistemology that is based on systems thinking and adaptive management as a foundation for participatory approaches. The M&E of ICTs faces a number of challenges including the lack of a unifying theoretical framework, the need to define users and purposes for each evaluation, the importance of agreeing on the type of causality that is expected, and the reality of short- term project durations. In response to these challenges I review established and emerging approaches such as Utilization Focused Evaluation, Outcome Mapping and Most Significant Change that embrace participation. Participation is a term open to many interpretations; to clarify its meaning I offer several ladders of participation. I conclude with a reflection on the conditions necessary for participatory approaches to gain acceptance in this field. A major lesson in participatory M&E is to understand the methods and to go beyond and be vigilant of the conditions that enable their application.
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 | 0.001 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".