jbv-methods — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited jbv-methods (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
JBV prizes a clear, substantive theoretical contribution to entrepreneurship over any single method. Well-executed qualitative, conceptual, quantitative, and mixed-method studies are equally welcomed; the unifying demand is that the work advance theory about the entrepreneurial phenomenon, not merely apply a method. Choose the design that can actually test or build your theory:
| Entrepreneurial question / claim | Fitting design |
|---|---|
| Process of how ventures emerge / sensemaking | Inductive qualitative (Gioia, process), longitudinal case studies |
| Entrepreneurial judgment / cognition under uncertainty | Experiments, conjoint/policy-capturing, vignettes (Prolific/lab) |
| Antecedents/consequences across many ventures | Archival venture panels (Crunchbase, PitchBook, GEM, KFS, PSED) |
| Founding choice, exit, IPO, failure | Survival/event-history; selection models |
| Financing signals (VC, crowdfunding) | Field/natural experiments, panel with funding events |
| Theory-building plus generalization | Mixed methods (qual to build, quant to test) |
The Editorial Manager workflow lets you attach a MethodsX article (detailed protocol) or Data in Brief descriptor on the "Attach files" page — useful for novel measures, hand-coded datasets, or experimental protocols.
For the empirical / causal lane, estimate and audit rather than only specify. Full map: execution-with-mcp. JBV studies founders and ventures where selection / survivorship threatens every claim; lead with identification and selection-correction tooling.
detect_design → recommend → fit with as_handle=true → audit_result toenumerate the checks the design owes.
callaway_santanna / sun_abraham + bacon_decomposition+ honest_did_from_result. IV: effective_f_test + anderson_rubin_ci. RDD: rdrobust + mccrary_test.
romano_wolf for the many-outcomefamily-wise correction reviewers expect.
Match the toolchain to the reviewer pool, and report the effect size the venue wants. A run end-to-end (synthetic data, real returns) is in the JF execution walkthrough.
| Pushback at the design stage | JBV-specific fix |
|---|---|
| "Cross-sectional, yet you theorize a venturing process." | Re-design with staged measurement or a pre/post shock; a single wave cannot carry a process claim. |
| "The construct is general-management ability relabeled." | Anchor the manipulation/measure to a venture primitive and show discriminant validity from it. |
| "Your sample is whoever survived to be observed." | Push the frame upstream to nascent/registry data capturing pre-founding and failed ventures. |
| "A novel hand-coded dataset — why trust the frame?" | Document construction, inter-coder reliability, and coverage; consider a MethodsX/Data in Brief co-submission. |
A hypothetical JBV study claims perceived environmental uncertainty causes founders to evaluate ambiguous opportunities more favorably. Design reasoning:
【Question→design fit】design chosen + why it fits the entrepreneurial claim ...
【Selection】founding-choice strategy ...
【Survivorship/attrition】sampling-frame handling ...
【Data novelty】construction + coverage + frame ...
【Temporal precedence】how ordered in time ...
【Artifacts】MethodsX / Data in Brief? ...
【Next step】jbv-data-analysis~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.