pith:3I2NNFLA
Career Mobility of Planning Alumni in the United States: Evidence from Professional Profile Data using Large Language Models
Planning alumni who pursue multisector experience and lateral industry switches achieve significantly higher upward mobility.
arxiv:2605.12618 v1 · 2026-05-12 · cs.CY
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\usepackage{pith}
\pithnumber{3I2NNFLAOBRUXDPJT6EJSPQCCD}
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Claims
planning alumni who adopt boundaryless career patterns, specifically multisector experience or lateral and industry-switching trajectories, achieve significantly higher upward mobility.
LinkedIn profiles provide a representative and unbiased sample of planning alumni careers, and large language model extraction accurately captures detailed career trajectories without significant errors or selection bias.
Analysis of LinkedIn profiles shows planning alumni with multisector or lateral career trajectories achieve significantly higher upward mobility.
References
Receipt and verification
| First computed | 2026-05-18T03:10:00.473394Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
da34d6956070634b8de99f88993e0210f9bfe0137b8a0228590aee6e28a383b1
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/3I2NNFLAOBRUXDPJT6EJSPQCCD \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: da34d6956070634b8de99f88993e0210f9bfe0137b8a0228590aee6e28a383b1
Canonical record JSON
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"license": "http://creativecommons.org/licenses/by/4.0/",
"primary_cat": "cs.CY",
"submitted_at": "2026-05-12T18:06:32Z",
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