Connext ED Foundation: A Study of Organizational Culture in a Foundation Contributing to Thai Educational Quality Enhancement
Bibliographic record
Abstract
This research analyzes the organizational culture of The Connext ED Foundation, a foundation established to develop Thai educational quality enhancement, and its impact on organizational success. Using qualitative methods, including in-depth interviews and content analysis, the study examines executives, employees, and foundation project participants. Findings reveal that the foundation integrates four organizational cultures: Clan Culture, fostering collaboration and engagement; Hierarchy Culture, ensuring structure and efficiency; Adhocracy Culture, promoting innovation and adaptability; and Altruistic Culture, driving social impact. This balanced cultural integration enhances employee engagement, operational efficiency, and sustainable innovation. Key enablers, such as visionary leadership, open communication, and flexible structures, create an environment conducive to long-term success. The study highlights how educational foundations and/or non-profit organizations can design a culture that harmonizes diverse values while prioritizing social good. These insights contribute to the broader understanding of cultural integration in educational foundations and/or non-profit organizations, emphasizing that a well-balanced culture fosters both internal effectiveness and external impact. The findings provide a framework for other organizations aiming to achieve sustainable social transformation through strategic cultural management.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".