Bespoke measurement: the evidence, the method, and the framework question

Working memo, 2026-08-31. All rows are verbatim from the v10 coded corpus (1,969 main-specification governance measures across 125 papers).

Definitions

Terms used throughout, each with exactly one meaning:

  • Form: the triple (level, resolution, named_procedure). All three are closed-vocabulary fields already coded on every measure. Two measures have the same form if and only if all three values match exactly. No text is read and no similarity judgment is involved.
    • level: the entity the variable is an attribute of, the smallest one that completes "this variable is an attribute of ___": director, board, committee, CEO, chair, firm, and so on.
    • resolution: what kind of number the construction produces, judged before any monotone transformation (a logged count is still a count): binary, categorical, ordinal, count, share (a part-of-whole ratio), or continuous.
    • named_procedure: the named statistical machinery beyond plain arithmetic, if any: none (levels, tallies, means, shares), concentration index (Blau, Herfindahl), spread statistic, pairwise comparison, graph position (centrality), faultline algorithm, latent weighting (factor/PCA), or model-derived.
  • Sub-construct: the content a measure claims, refined below the coded construct. Financial expertise and technology expertise are different sub-constructs. Measuring different sub-constructs is legitimate specialization, not the bespoke problem.
  • Quantity: the target a measure aims at, given by two coordinates: the entity whose attribute it is (director, CEO, chair, board, firm, industry, country) and the aspect of that entity the number is about, one of:
    • individual status: an attribute of one person (this director is a woman).
    • group composition: the prevalence of an attribute among a group's members: shares, counts, any-member indicators, majority or critical-mass indicators.
    • group heterogeneity: the mixture across three or more categories of an attribute. For a binary attribute, a diversity index such as the Blau index is a deterministic function of the share and is classified as group composition; group heterogeneity is reserved for multi-category attributes.
    • relational: ties, similarity, or comparisons defined against specific other actors.
    • context attribute: a property of an environment rather than of persons or member groups (a country quota law, an industry exposure).
    Director gender and board gender composition are different quantities of the same construct. Measuring different quantities is legitimate specialization, not the bespoke problem.
  • Definition: within a sub-construct and quantity, the raw facts that identify the attribute: what is counted, over whom, with what classifier, against what denominator, over what window. Three studies of financial expertise that use education, a CFO title, and industry tenure are three definitions of one sub-construct. That is the bespoke problem.
  • Raw count: the number of distinct forms (or distinct definitions, or distinct quantities) observed in the corpus for a construct. Each distinct value contributes one to the raw count, whether it is used by one measure or by fifty.
  • Effective number: a raw count can be large solely because many variables are defined in a unique way a single time in the corpus. To show whether a large raw count reflects such singleton usage or disagreement across many papers, we also report the effective number: the inverse Simpson index 1 / Σ pi2, where pi is the share of measures using category i. The effective number equals the raw count when usage is spread evenly and approaches one as usage concentrates in a single category.

The full hierarchy is construct → sub-construct → quantity → definition → form. Apparent measurement heterogeneity within a construct therefore decomposes into three components with different interpretations: variety of quantities (researchers ask different questions about the same construct; legitimate), dispersion of definitions within a quantity (the bespoke problem proper), and dispersion of forms within a quantity and definition (residual inconsistency in how one definition is rendered as a number).

One measure, classified at every layer

The measure PCTFINEXP (van_peteghem_et_al_2018), coded verbatim as: Number of board members qualifying as financial experts under SOX divided by total board members.

LayerValue for this measureWhat the layer records
Constructexpertisethe coded content field: the broad attribute family the paper invokes
Sub-constructfinancial/accounting expertisethe content the measure claims, refined: financial expertise, not technology or legal expertise
Quantityboard composition of expertsthe target: whose attribute (the board) and which aspect (the prevalence of the attribute among its members)
DefinitionFirm-designated (SOX/audit-committee) financial expertthe facts that identify the attribute: the SOX financial-expert designation, rather than a CPA credential, a CFO career, or a vendor flag
Formboard · share · nonethe number produced: a board-level share, built with no named procedure

Why form alone is a lower bound

Counting distinct forms within a construct requires no judgment and is computable now. It is a strict lower bound on the number of distinct operationalizations, because it treats everything inside one form cell as identical, however different the underlying definitions are. The following four measures, all from the analytic sample, share the single form director | binary | none and are therefore counted as a single form by the lower bound. They are four distinct definitions of financial expertise:

PaperVariableFormOperationalization
gow_et_al_2018Financial Expertdirector | binary | noneIndicator equal to 1 if the reporting firm classifies the director as a financial expert, and 0 otherwise.
donelson_et_al_2025CPAdirector | binary | noneIndicator equal to one if the director is a certified public accountant or equivalent, and zero otherwise.
chen_et_al_2020Director with finance experience (indicator)director | binary | noneOne if before appointment the director held a CFO or treasurer title or worked in banking, finance, or investment firms, and zero otherwise.
field_et_al_2020Finance experiencedirector | binary | noneIndicator equal to one if either ISS or BoardEx reports that the director has finance experience.

The distinction also runs the other way. These two measures have different forms and would count as two under the lower bound, yet they share one quantity (board independence composition) and one definition (directors classified as independent, over board size), differing only in whether a threshold is applied:

PaperVariableFormOperationalization
adams_et_al_2018Board independenceboard | share | noneNumber of independent directors divided by board size.
huang_hilary_2018Independent Boardboard | binary | noneIndicator equal to one if a majority of board directors are classified as independent.

Form and definition are therefore separate axes. Counting definitions requires reading the operationalization text and making judgment calls; the Coding pilot section describes how those judgments are made.

Data: v10 coded corpus (128 papers, 7,601 records; 1,969 main-specification governance measures across 125 papers), loaded through the same corpus loader that builds the manuscript tables; primary constructs only. Form statistics are computed mechanically from the closed-vocabulary fields. Sub-construct, quantity, and definition classifications are a single uncalibrated LLM draft pass, described in the Dispersion evidence section. Nothing in the repository was modified.