Transaction Cost Theory in the Public Sphere: Using a Governance-Focused Analytical Lens to Solve Problems in K-12 Schools
Bibliographic record
Abstract
Public sector organizations, particularly K-12 schools, frequently struggle with organizational inefficiencies driven by complex governance issues and competing interests that impede student success. This dissertation addresses these challenges by advancing a strategic management perspective, employing Transaction Cost Theory (TCT) as a novel, governance-focused analytical lens. TCT, traditionally applied to the private sector, examines how organizations design governance mechanisms to mitigate coordination and cooperation hazards under the core behavioral assumptions of bounded rationality and bounded reliability. The work is presented in three progressively specific essays. Essay 1 establishes the theoretical foundation by reviewing TCT's origins, tracing its development through international business and family firm literature, and justifying its application to the public sphere by revealing a significant gap in the empirical record. Essay 2 demonstrates TCT's utility through a re-analysis of William Ouchi's Making Schools Work (2003), finding that the superiority of decentralized school governance is achieved by reducing bounded rationality and bounded reliability hazards. This essay also introduces responsibility ambiguity as a novel expression of incomplete information relevant to TCT research. The dissertation culminates in a qualitative empirical study addressing a critical, timely operational problem: How can different governance practices facilitate the successful integration of newcomers into K-12 schools? This issue is highly salient in the current institutional environment of Edmonton, Alberta, characterized by rapid immigration-driven population growth. Utilizing semi-structured interviews with principals from diverse public and charter schools, the research compares how these two discrete governance models strategically manage the high transaction costs of integration. The conclusion identifies two necessary conditions for newcomer success: i) ensuring schools are safe and orderly learning environments, and ii) providing flexible English as an additional language (EAL) programming. The analysis revealed that charter schools offer advantages in contract flexibility and securing philanthropic resources, while large public school divisions benefit from a strategic scale advantage. Ultimately, the research develops strategic recommendations for practitioners by identifying valuable lessons and governance mechanisms that each school type can learn from the other. The dissertation thus contributes to the empirical record of TCT in the public sphere and offers actionable solutions to support newcomer students today.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.018 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".