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\section{Research Applications and Identification Limits}\label{sec:applications}
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\subsection{What the database can support}

Four families of empirical designs are natural once the validation gates are passed; each is listed with the restriction it must respect.

\paragraph{Project counts and composition as firm-year variables.} The issuer-year count of newly observed projects, by category, is a text-derived measure of disclosed strategic activity comparable in spirit to the thematic scores of the factor layer but with a discrete, interpretable unit. Because the panel is a snapshot universe, firm fixed effects and within-firm comparisons are safer than cross-sectional levels, and the later entry of smaller issuers (Figure~\ref{fig:coverage}) should be modeled explicitly.

\paragraph{Technology adoption and diffusion.} The \texttt{technologies} field and the categories \texttt{ai\_initiative}, \texttt{data\_center}, \texttt{cloud\_migration}, \texttt{automation} and \texttt{erp\_implementation} allow the first-mention date of a technology to be located by issuer, sector and location, in the spirit of \citet{kalyani2025} but from the issuer's own regulatory narrative. The small counts of these categories (a few hundred projects each) and the fact that technologies are free-text tags rather than a controlled vocabulary limit precision; a mapping of tags to a vocabulary is part of the proposed ontology work.

\paragraph{Event studies.} Mentions in 8-K filings are dated to the day and are the closest the database comes to an announcement date (74{,}594 mentions). Because the primary document of an 8-K often refers to a press release filed as an exhibit that the pipeline does not read, the first \emph{public} announcement may precede the first mention in the corpus; event dates should be verified against the exhibit or the newswire before use.

\paragraph{Project-level panels.} For projects with several mentions, the timeline provides a sequence of status and amount statements that can be used to study announcement-to-completion durations, budget revisions and abandonment, subject to the caveats on status (last statement, not terminal fate) and on merged phases.

\subsection{Identification limits}

\begin{itemize}
\item \textbf{Disclosure, not activity.} The database measures what issuers chose to say in a regulated document. Disclosure thresholds, materiality judgments, boilerplate habits and litigation risk vary by firm, sector and time; a difference in project counts is a difference in disclosure before it is a difference in investment.
\item \textbf{Snapshot universe.} Survivorship and backfilling are built in. Comparisons across years that mix cohorts of issuers confound activity with the composition of the observed panel.
\item \textbf{Measurement error of unknown structure.} Until the human-coded evaluation is run, extraction precision and recall, category accuracy and linkage error are unknown. They are unlikely to be classical: boilerplate-heavy sectors and long MD\&As are more exposed to false positives and to truncation, respectively.
\item \textbf{Amounts.} Disclosed amounts are heterogeneous in type and scope and are never realized expenditure; the project-level maximum is a reading convenience, not an estimate.
\item \textbf{Descriptive versus causal.} Associations between project disclosures and outcomes (returns, investment, employment) identify the joint determination of disclosure and outcomes, not the effect of the project. Causal designs require a source of variation in the \emph{project} that is orthogonal to the decision to \emph{describe} it, and the database does not supply one.
\end{itemize}