From discourses on student learning and achievement to leadership practices: The case of Haitian educational leaders.
Bibliographic record
Abstract
This research’s main purpose is to study Haitian educational leaders’ leadership enactments in their schools. Objectives were elaborated to guide the study: describe leaders’ conceptualization of student learning and achievement (SL/A); describe their supports, challenges and obstacles. The research is based on this primary question: “How do educational leaders translate their understandings of SL/A into leadership practices?” The theoretical framework provided “thinking tools” to analyze the multiple dimensions of Haiti’s educational leadership, engaging with Bourdieu’s concepts (field, habitus, capitals, strategies) through a Theory of School Leadership Practice (Eacott, 2013). Located within the Comparative and International Education field (CIE), this qualitative case-study delved into the multi-faceted situations of Haitian principals using methods like semi-structured interviews, non-participant observations, and documents. Among the data gathered, one of the emergent themes discusses educational leaders as individuals and principals, considering how both features impact their leadership practices. Although more studies in educational leadership employed Bourdieu’s concepts, this is not the case within scholarship on/about Haiti’s education system, especially its educational leadership. Therefore, that constitutes an important and unique contribution to the fields of CIE and educational leadership, especially relating to Haiti.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.019 | 0.018 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| 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".