The Changing Role of the Evaluator in the Process of Organizational Learning
Bibliographic record
Abstract
Abstract: In this article we examine the role of the evaluator in the process of organizational learning, and discuss the conditions necessary to facilitate the productive execution of such a role and the consequent ramifications for evaluation. First, we describe the process of organizational learning as presented in the literature of organizational learning. Second, we examine the demands that process presents to evaluators. Third, we discuss organizational learning within the context of participatory evaluation, and then explore the role of the external learning agent. Finally, we present some major changes in the role of the evaluator, changes that stem from the very nature of the organizational learning process. The focus on organizational learning transforms the role of the evaluator to one of knowledgeable facilitator who returns responsibility of the operation, development, and evaluation back to the project/program or organization. We conclude by acknowledging the difficulties involved in changing the traditional role of the evaluator, particularly in giving up control of the evaluation to the stakeholders and letting the organization become the “owner” of the evaluation process and knowledge, leaving the evaluator the important role of facilitator. The evaluator is responsible for the procedures of learning — providing tools and monitoring the learning that goes on. The learning content is the responsibility of the organization and not of the evaluator. While we do not preclude the traditional role of the evaluator, we do suggest a significant change in the procedures involved in evaluation, in the skills required to conduct effective evaluations within the organizational context, and in the ownership of the knowledge that emerges from such evaluation.
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 | 0.075 | 0.077 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.023 |
| Scholarly communication | 0.020 | 0.014 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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; 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".