Is the GED an Effective Route to Postsecondary Education for School Dropouts?
Bibliographic record
Abstract
We use data from the Texas Schools Microdata Panel (TSMP) to examine the extent to which dropouts use the GED as a route to post-secondary education. The paper develops a model pointing out the potential biases in estimating the effects of taking the "GED path" to postsecondary education. Lacking suitable instruments that would allow us to directly address potential biases, our approach is to base our estimates on a set of academically "at risk" students who are very similar in the 8th grade. We observe that the eventual high school graduates in this group have much better postsecondary education outcomes than do the similar at-risk 8th graders who dropped out and obtained a GED. Our model explains the observed differences, and allows for a discussion of the policy challenges inherent in improving the postsecondary outcomes of dropouts.
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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 | 0.010 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".