Higher Education, Human Development and Growing Inequality in Pre- and Post-Pandemic Haiti
Bibliographic record
Abstract
For almost four decades, Haiti has been engaged in the tenuous process of democratization, exacerbated by political, economic, social, climate, and more recently the COVID-19 crises. With each crisis, efforts are made to reimagine national development and revitalize the public sphere, with limited success. Yet, largely absent from these debates is the higher education sector. We argue that the neglect of higher education since Haiti’s transition from dictatorship to democracy is a result of the nation’s failure to articulate a clear vision for the sector. In this article, we ask: How has the failure to articulate a clear purpose for the higher education sector in Haiti exacerbated the country’s systemic crisis amid the COVID-19 pandemic? In order to answer this question, we provide a sociohistorical examination of the role of power and politics in Haitian higher education beginning in its founding in the 19th century culminating at the time of the pandemic. We explore how the absence of a strategic vision for higher education institutions in Haiti and ad-hoc neoliberal policies have impacted the professoriate and students while impeding the sector’s potential contributions to society in a time characterized by systemic and uninterrupted crises including the COVID-19 pandemic.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".