A Path Analysis of the Antecedents, Business Sustainability Practices and Outcomes of Private Schools in the Philippines
Bibliographic record
Abstract
According to the Organization for Economic Cooperation and Development, early childhood education results in long-term social and economic benefits; thus, governments must ensure that elementary and secondary schools can survive disruptions in the business environment as the education sector should not be compromised especially in a developing country. In a world characterized by drastic and disastrous changes, a resilient and sustainable education sector must always be ensured. Adopting sustainability initiatives appears to be the key to survival in response to the negative effects of various external factors affecting the world. The purpose of this study is to examine the causes and consequences of business sustainability practices in private elementary and secondary schools in the Philippines. The findings revealed that regulatory policies, science and environment, and customer demand are vital predictors for private schools’ sustainability practices, with significant impact on their outcomes. Although the relationships between antecedents, sustainability practices, and outcomes were positive, they were moderate and weak respectively. The study further showed that the private schools’ sustainability practices have a significant mediating effect between the antecedents and outcomes of the private schools’ sustainability.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".