Hispanic Serving Institutions after a Quarter Century: Charting the Course for the Future
Bibliographic record
Abstract
The number of Hispanic Serving Institutions (HSIs) have more than tripled in the U.S. between 2000 and 2020. In 2000, there were 229 HSIs. By 2020, there were 569 HSIs and 333 emerging HSIs, for a total of 902. Although HSIs make up only 18% of all U.S. colleges and universities, they enroll 67% of the Latino students. This paper examined the ramifications of such rapid growth. A scoping review of the literature revealed two major themes: Establishing an HSI Identity and Issues Associated with Enrollment, Transfer, and Degree Completion over the past 25 years. The publications reviewed addressed challenges including the need for more faculty diversity, transparency in the use of funds, and the need for HSIs to be more Hispanic serving. The implications of the findings are discussed and recommendations for the future of HSIs are offered.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.013 | 0.017 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".