spb/firc0001_uqo

1% ============================================================================2\section{Introduction}3% ============================================================================45A large share of what firms do strategically---build plants, open data centers, integrate acquisitions, launch products, move systems to the cloud, commit to decarbonization targets---is described, often repeatedly and over several years, in the narrative sections of their regulatory filings. Yet the standard quantitative record of corporate investment is an aggregate: capital expenditure, R\&D expense, acquisitions, or counts of patents and plants. Researchers who want to observe the \emph{unit of decision}---a specific, identifiable initiative with a start, a scope, a budget and a fate---have had to assemble hand-collected samples, rely on commercial databases with opaque coverage, or infer initiatives indirectly from word frequencies. This paper documents an attempt to build that unit systematically, from primary sources, for a broad cross-section of U.S.-listed companies.67The object we describe is SPID (\emph{SEC Project Intelligence Database}), developed at the Université du Québec en Outaouais on top of the UQO EDGAR research corpus. Its first release, in June 2026, covered the 500 constituents of the S\&P~500 \citep{spid2026}. The present paper documents its extension, carried out on October~27--28, 2026, to an issuer universe that approximates the Russell~3000: 2{,}564 distinct SEC registrants, 527{,}548 annual, quarterly and current reports filed between January 2010 and October 2026, 1.12 million filing sections submitted to a schema-constrained large-language-model (LLM) extractor, and 308{,}065 resulting project mentions resolved into 121{,}099 candidate projects. Every retained mention carries the SEC accession number, the section identifier and a model-generated description grounded in the source passage, so that any number in the database can be traced back to a public document.89Our core research question is methodological: can we reliably identify, classify, date, link and quantify distinct strategic projects disclosed by Russell~3000 companies, while preserving source evidence and without claiming exhaustive coverage of real-world activity? The answer offered here is deliberately two-sided. On the positive side, the pipeline is reproducible end to end, every intermediate artifact is versioned, and the full corpus has been processed with a single extraction contract and an audit ledger that records which sections were seen. On the cautious side, several components that a fully validated measurement instrument requires---an independent human-coded gold standard, precision and recall estimates by category and field, an audit of cross-filing linkage---are specified in this paper but have not yet been executed at scale. We therefore describe SPID as a \emph{research database under validation}, and we keep a running register that separates implemented, documented-but-unverified, proposed and empirically verified claims (Appendix~\ref{app:evidence}).1011The paper makes four contributions. First, it specifies the measurement target precisely: a \emph{project} is a distinct, identifiable, issuer-associated strategic initiative described in one or more disclosures, as opposed to a \emph{project mention} (a particular sourced statement), a \emph{generic strategy} (``we invest in innovation''), a historical or third-party reference, or an uncertain candidate. Section~\ref{sec:construct} develops these distinctions and ties them to the existing 21-category SPID taxonomy, which we document rather than redesign. Second, it documents a scalable architecture: a frozen issuer universe reconciled against SEC identifiers; an acquisition layer that respects the SEC's fair-access limits by sharing one aggregate rate budget across ten cluster nodes and one external gateway; a parser that keeps raw-to-clean-text provenance; and an extraction ledger that makes the paid inference step resumable and idempotent (Section~\ref{sec:architecture}). Third, it exposes the extraction contract and the resolution rule in enough detail to be criticized: the prompt, the JSON schema, the confidence semantics, the deterministic project key, and the ways in which that key can both split and merge real initiatives (Section~\ref{sec:resolution}). Fourth, it lays out a validation protocol and a set of acceptance gates, and reports what the current build does and does not satisfy (Section~\ref{sec:validation}).1213Three caveats frame everything that follows. A present-day holdings file of an index-tracking fund is a proxy for index membership, not an authoritative historical constituent list; the universe is a snapshot, and survivorship is built into it (Section~\ref{sec:sample}). A disclosed project is evidence that an issuer \emph{described} an initiative, not evidence that the initiative happened, and a disclosed budget is a statement about intentions or estimates, not realized capital expenditure. Finally, the extractor only sees what the parser gives it: sections that were truncated, filings that failed to download, and exhibits outside the selected forms are invisible, and ``zero projects'' for an issuer-year must never be read as ``no projects''.1415The rest of the paper is organized as follows. Section~\ref{sec:literature} positions the work in the text-as-data, corporate-investment and information-extraction literatures. Section~\ref{sec:sample} defines the universe and reports its reconciliation. Section~\ref{sec:architecture} describes acquisition, parsing and the distributed build. Section~\ref{sec:construct} defines the project construct and the extraction contract. Section~\ref{sec:resolution} covers mention-to-project resolution, timelines and amounts. Section~\ref{sec:results} reports descriptive patterns. Section~\ref{sec:validation} presents the validation framework and the current audit. Section~\ref{sec:applications} discusses research applications and identification limits, and Section~\ref{sec:conclusion} concludes. Appendices provide the taxonomy, the data dictionary, the prompt, the evidence register and replication instructions.16