Measuring Performance for Accountability of a Small Social Economy Organization: The Case of an Independent School
Bibliographic record
Abstract
ABSTRACT This article is a result of a joint project in social economy research between a community partner-an independent school-and academic partners. The school is a democratic organization, run by teachers and parents. The goal of the project was to find ways to improve communication and reporting about general performance of the school as part of the school's accountability to its members. Starting from lessons of the balanced scorecard approach for non-profits, we describe the process of development of survey-based measures for the particular organization. The direction of the tool development and subsequent organizational changes were carried out in a participatory process between the school's staff, the parents, and the board. We identify the limitations and challenges of this process, and outline its successes to draw lessons for other similar democratic organizations. RÉSUMÉ Cet article est le produit d'un projet conjoint de recherche sur l'économie sociale entre un partenaire communautaire-une école privée-et des partenaires académiques. L'école est une organisation démocratique dirigée par des enseignants et des parents. Le but de ce projet était de trouver des façons d'améliorer la communication et la reddition de compte en ce qui a trait au rendement général de l'école comme faisant partie de la responsabilité de l'école envers ses membres. En commençant par des leçons sur l'approche de tableau de bord équilibré pour les organismes sans but lucratif, nous abordons le processus de l'élaboration de mesures fondées sur des enquêtes pour l'organisation particulière. L'orientation du développement d'outils et des changements organisationnels subséquents ont été déterminés lors d'un processus participatif entre le personnel de l'école, les parents et la direction. Nous établissons les limites et les défis de cette façon de procéder et en soulignons les réussites pour tirer des leçons qui serviront à d'autres organisations démocratiques comparables.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".