Llama-3.2-3B-Instruct full-cohort baseline (prompt v1)

vLLM digital-twin results on the original 5-tier Terrarium prompts

Model: meta-llama/Llama-3.2-3B-Instruct · Prompt generation: pre–v3.1 packaging (version 1 core ladder)
Companion: Cross-model memo · Llama-3.1-8B · DeepSeek · Llama-3.3-70B · Prompt version map

Same prompt v1 ladder and N=241 cohort as the 8B baseline. A Llama-3.2-3B (base) run only parsed ~7% of outputs; this page is the Instruct counterpart used for evaluation.


Model tag: llama32_3b_instruct
Sample: N = 241 × 5 tiers = 1205 prompts
Parse success: 1205/1205 (100.0%)
Throughput: 20.97 samples/s (~57.5s)
Export: psych755_vllm_llama32_3b_instruct_full_cohort_20260726_0252


1 1. Research questions

  1. RQ1 — Employment: Does employment context reduce absolute PRCA error vs demos?
  2. RQ2 — Transit: Do transportation cues improve CA prediction / change error?
  3. RQ3 — Full context: Does cumulative context improve recovery / alter stereotyping?

Tracked metrics: MAE, exact score match, band accuracy, band distance, signed mean error.


2 2. Executive interpretation

Across 1,205 predictions:

Metric Observed Naive baseline Verdict
Exact group 9.1% ~4% Above chance
Exact interpersonal 7.7% ~4% Above chance
Band group 52.7% ~33% Above chance
Band interpersonal 30.0% ~33% At/below chance
MAE group 5.51 Still large vs classical ML floor (~4.5)
MAE interpersonal 5.35 Still large

RQ1: Employment vs demos: group MAE 5.59→5.59 (Δ 0.00); IP 5.07→5.25 (Δ 0.18).

RQ2: Transit vs demos: group MAE 5.59→5.47 (Δ −0.12); IP 5.07→5.65 (Δ 0.58); IP band 29.5%→29.5%.

RQ3: Full vs demos: group MAE 5.29 vs 5.59; group band 53.9%→50.6%; IP MAE 5.07→5.53; IP band 29.5%→31.5%.


3 3. Comparison vs Llama-3.1-8B-Instruct (same prompts/cohort)

Metric (all tiers) 3B-Instruct 8B-Instruct
MAE group 5.51 5.92
MAE interpersonal 5.35 5.82
Band acc group 52.7% 28.8%
Band acc interpersonal 30.0% 40.2%

On this v1 ladder, the 3B Instruct model has lower MAE and much higher group band accuracy than 8B Instruct, while 8B leads on interpersonal band accuracy.


4 4. Metrics by tier

tier n mae_group mae_interpersonal exact_group band_group exact_IP band_IP
all 1205 5.51 5.35 9.1% 52.7% 7.7% 30.0%
demos 241 5.59 5.07 8.3% 53.9% 7.5% 29.5%
employment 241 5.59 5.25 8.7% 53.5% 7.9% 29.0%
geo 241 5.63 5.27 8.7% 52.7% 7.9% 30.3%
transit 241 5.47 5.65 8.3% 52.7% 7.5% 29.5%
full 241 5.29 5.53 11.2% 50.6% 7.9% 31.5%

4.1 Deltas vs demos

tier Δ MAE group Δ MAE IP Δ band group Δ band IP
employment 0.00 +0.18 −0.4 pp −0.4 pp
geo +0.04 +0.21 −1.2 pp +0.8 pp
transit −0.12 +0.58 −1.2 pp 0.0 pp
full −0.29 +0.46 −3.3 pp +2.1 pp

5 5. Band confusion (all tiers)

5.1 Group

gt_band low moderate high
low 620 30 0
moderate 290 15 0
high 246 4 0

5.2 Interpersonal

gt_band low moderate high
low 54 558 28
moderate 38 299 8
high 38 174 8

6 6. Success checklist

Criterion Result
Schema-valid CA JSON Yes (100%)
Exact digital-twin recovery No (single-digit exact rates)
Coarse band recovery Partial — group above chance; IP at/below chance
RQ1 employment helps Negligible MAE change
RQ2 transit helps Small group MAE gain; IP MAE worse
RQ3 more context helps Mixed; full lowers group MAE, IP mixed