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Record W4366451556 · doi:10.3138/cjpe.020.004

The Changing Role of the Evaluator in the Process of Organizational Learning

2005· article· en· W4366451556 on OpenAlexvenueno aff
Miri Levin‐Rozalis, Barbara Rosenstein

Bibliographic record

VenueCanadian Journal of Program Evaluation · 2005
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsFacilitatorOrganizational learningKnowledge managementProcess (computing)Context (archaeology)Organization developmentParticipatory evaluationPsychologyComputer scienceProcess managementSocial psychologyBusinessSociology

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.027
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.746
Threshold uncertainty score0.953

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0270.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.125
GPT teacher head0.479
Teacher spread0.354 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2005
Admission routes1
Has abstractyes

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