Will the Working Poor Invest in Human Capital? A Laboratory Experiment
Bibliographic record
Abstract
This paper presents the results of a laboratory experiment involving some 250 subjects in the Montreal area. The experiment focused on three main questions : (1) Will the working poor invest in various assets? (2) Are these subjects willing to delay consumption for substantial returns? (3) How do these subjects view risky choices? Answering these questions will help answering the key research question : Given the right incentive, will the working poor save to invest in human capital? To view the report, please click here : http://www.srdc.org/publications/Will-the-Working-Poor-Invest-in-Human-Capital-A-Laboratory-Experiment-details.aspx Ce rapport présente les résultats d'une expérience en laboratoire impliquant environ 250 sujets résidant dans la région de Montréal. L'expérience tente de répondre à trois questions : 1) Les travailleurs à faible revenu investissent-ils dans des actifs diversifiés?; 2) Les sujets sont-ils prêts à reporter leur consommation dans le futur en échange de rendements financiers substantiels?; 3) Comment ces sujets perçoivent-ils les choix risqués? Les réponses à ces questions vont permettre d'éclairer le sujet principal de cette recherche menée par le SRDC, à savoir : Si on leur procure les bonnes incitations, les travailleurs à faible revenu auront-ils tendance à épargner pour investir dans du capital humain? Pour visionner l'intégralité du rapport cliquez ici : http://www.srdc.org/
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| 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".