agentsclimarketplace

Demog theory building

Skill brycewang-stanford/Awesome-Journal-Skills/Demography-Skills/skills/demog-theory-building

Use when building the argument of a Demography (PAA / Duke University Press) manuscript into a population-science contribution — whether the work is formal/mathematical demography, an explanatory account of fertility/mortality/migration, or a measurement/decomposition advance. Demography rewards a clear mechanism or a sharpened estimate over a bare correlation. Structures the argument; it does not run analyses.From its SKILL.md

Install
npx -y skills add brycewang-stanford/Awesome-Journal-Skills --skill demog-theory-building

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

SKILL.md

6.1 KB, ~1.2k tokens by cl100k_base, as published. Nobody here has run it

Theory & Argument Building (demog-theory-building)

At Demography a result is not a contribution until it is attached to a claim population science can use — a mechanism that explains a demographic process, a sharper estimate that revises the record, or a formal result that unifies or clarifies. This skill turns findings into argument: explicit mechanisms, scope conditions, and observable implications, in the idiom appropriate to your kind of work.

When to trigger

  • The empirics are strong but the "so what / why" is thin
  • A reviewer said the paper is "descriptive," "atheoretical," or "just a correlation"
  • You need to state mechanisms, identifying assumptions, or scope conditions explicitly
  • Formal demography: deciding what to model and what the model buys you

Build the argument (by mode of work)

Explanatory population study

  1. Concept & measure — define the demographic construct (e.g., parity progression, lifespan inequality, net migration) precisely; distinguish it from neighbors and from its measure.
  2. Mechanism — the population story: which behaviors, exposures, or compositional shifts move the rate, for whom, and why (incentives, constraints, selection, cohort experience).
  3. Observable implications — what we should see if the mechanism operates (age pattern, cohort signature, subgroup contrast) and what we should not see. These become the tests in demog-research-design.
  4. Scope conditions — which populations, periods, and regimes the argument covers.

Formal / mathematical demography

  • State the substantive population puzzle the model addresses before the setup.
  • Keep assumptions (stability, stationarity, Markov transitions, independence) transparent and motivated; flag which results depend on which assumptions.
  • Translate results into interpretable demographic quantities (e.g., contributions to life expectancy, sensitivities/elasticities, equilibrium structure) a reader can recognize.
  • Say what the model buys: a non-obvious decomposition, a unifying identity, a corrected intuition.

Measurement / decomposition contribution

  • Make explicit what the new measure or decomposition separates that prior work conflated (e.g., tempo vs. quantum, composition vs. rate, age vs. cohort).
  • Show the substantive payoff: the trend now attributes to a different component than was assumed.

The "portability" test (Demography-specific)

Ask: Could a demographer studying a different component or population import this mechanism, measure, or decomposition? If yes, you have a population-science contribution. If it only works for your exact case, generalize the logic or reframe (back to demog-topic-selection).

Anti-patterns

  • "Hypothesizing after results are known" — state the argument before the tests
  • A formal model with opaque assumptions chosen to produce the desired identity
  • Mechanisms named but never made observable in age/cohort/subgroup patterns
  • Treating a regression coefficient as a mechanism with no demographic story
  • Universal claims with no scope conditions on population, period, or regime

Worked micro-example: from finding to population-science claim (illustrative)

A hypothetical study observes that completed cohort fertility fell across successive birth cohorts. The argument is built in the idiom Demography — the Population Association of America flagship at Duke University Press — rewards (numbers invented to illustrate):

  • Bare finding: "Cohort TFR fell from ~2.1 to ~1.7 across the 1955-1975 birth cohorts."
  • Mechanism: Postponement of first births raised the mean age at first birth, and recuperation at older ages was incomplete — a quantum decline operating through tempo, not a uniform shift.
  • Observable implication: Parity-progression ratios from parity 0 to 1 should fall most at younger ages and only partly rebound later; a pure quantum story would show uniform decline across ages.
  • Scope condition: The claim covers low-fertility settings with delayed childbearing.
  • Portability: A mortality scholar can import the tempo-vs-quantum logic to lifespan compression; that import makes it a population-science contribution, not a single-country fact.

Referee-pushback patterns and the theory-side fix

  • "This is descriptive — where is the mechanism?" -> Name the behavior/exposure/compositional shift that moves the rate, for whom, and translate it into an age or cohort signature the design can test.
  • "You assert a mechanism but a compositional shift would produce the same trend." -> State the rival (composition) explicitly and the observable that separates it from your account before the results.
  • "The formal model's assumptions are chosen to deliver the identity." -> Flag which results depend on stability/Markov/independence assumptions and motivate each substantively.
  • "This only works for your one case." -> Generalize the mechanism so another demographer studying a different component could reuse it; otherwise reframe via demog-topic-selection.

Output format

【Core claim】one sentence
【Mechanism / identity】the population story or formal result
【Assumptions】(formal) the load-bearing ones
【Observable implications】testable demographic signatures -> research-design
【Scope conditions】which populations / periods it covers
【Portability】who else in population science can use this
【Next】demog-research-design

Supplementary resources

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.