Facilitating Development of Organizational Productive Capacity: A Role for Empowerment Evaluation
Bibliographic record
Abstract
Abstract: Efficacy of community-based social programs is highly dependent on the development of organizational and program capacities — capacities which include the domains of (a) a core-empowered group, (b) internal resources organization, (c) external resources mobilization and integration, (d) strategy comprehensiveness and logic, and (e) monitoring, evaluation and feedback. A framework is offered in which organizational productivity and program outcomes are conceptualized as a product of a transformational process, in which organizational capacities transform vision into productive activity, using the resources of an organization and activated through an environment of collective empowerment. Collective empowerment is defined by the authors as an energy force of mutual commitment, cohesiveness, and conscientiousness that activates the development of increasing organizational capacities, through a cyclical process that builds increasing commitment, “small wins,” and expanded membership. Collective empowerment contributes to the expansion of the program effort with concomitant increased activity accomplishment and achievement of intended outcomes. The authors argue that empowerment evaluation is a philosophy and set of practices that contributes to the development of collective empowerment as well as to the development of organizational and productive capacities. Empowerment evaluation must simultaneously keep in mind the intended program outcomes (which need to be reliably measured) in order to justify the original goals of the program and ensure continuous learning and benefit. Guidelines for evaluators using the empowerment evaluation model are provided.
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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 | 0.093 | 0.100 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".