Disentangling Motivation and Study Productivity as Drivers of Adolescent Human Capital Formation: Evidence from a Field Experiment and Structural Analysis
Bibliographic record
Abstract
We estimate a structural model of endogenous short-run human capital investment focusing on a learner’s leisure-study choices, influenced by external costs/benefits and two key internal factors: learning productivity and willingness to engage in study activity. Our novel self-investment framework rigorously quantifies models of learning that have existed in the psychology literature for decades. Our identification strategy combines panel data and study-incentive variation to point identify student-level parameters. Empirically, we find that idiosyncratic productivity and motivation traits are uncorrelated, and that low productivity is the stronger predictor of academic struggles, not low motivation. We investigate the influence of external factors on student learning and find that school quality affects it through 3 channels: augmenting productivity, augmenting skill production TFP, and by altering the mapping between learning activity and permanent skill gains.
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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 | 0.002 | 0.001 |
| 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".