Summary Tables
Part of Census and Demographics
Condensing raw census data into concise tables that decision-makers can read and act on at a glance.
Why This Matters
Raw census data is a collection of individual records. It answers questions about specific people. But most governance decisions are not about individuals — they are about aggregates. How many working-age adults do we have? What is the ratio of productive workers to dependents? How has our population changed since last year?
Summary tables transform the raw data into the aggregate form that governance actually uses. A well-designed summary table communicates in seconds what would take an hour to extract from individual records. It makes the key numbers visible to everyone in the community, not just the recorder who knows where to look in the ledger.
Summary tables are also the form in which census data is shared between communities, reported to external authorities if relevant, or compared across time periods. A table from this year and a table from two years ago on the same sheet allows immediate comparison without referencing raw records.
The investment in producing clean summary tables pays off every time a governance decision is made. Decision-makers who can see the numbers make better decisions than those who must operate on memory and intuition.
Core Summary Tables for Post-Collapse Communities
Table 1: Population Summary
The most basic and most used table. Produced at each census, it should be posted publicly.
| Category | Count | % of Total |
|---|---|---|
| Total population | 100% | |
| Children under 5 | ||
| Children 5–14 | ||
| Adults 15–59 | ||
| Adults 60+ | ||
| Male | ||
| Female | ||
| Total households | ||
| Average household size |
This single table answers the most common questions: total population, demographic distribution, sex ratio, household count. It should fit on one page or be readable on a posted notice.
Table 2: Labor Capacity Summary
| Labor Tier | Count | Notes |
|---|---|---|
| Tier A: Full capacity, unencumbered | ||
| Tier B: Full capacity, caregiving obligations | ||
| Tier C: Limited capacity | ||
| Tier D: Dependent | ||
| Total available labor (A+B+C) | ||
| Dependency ratio (D / A+B+C) |
The dependency ratio is a single critical number: how many dependents must each productive person support? A ratio above 1.0 (more dependents than workers) indicates serious structural stress. A ratio below 0.3 indicates a high-capacity, low-burden population.
Table 3: Skills Summary
| Skill Domain | Expert | Competent | Novice | Critical Gap? |
|---|---|---|---|---|
| Medical/healing | ||||
| Agriculture | ||||
| Animal husbandry | ||||
| Construction | ||||
| Metalworking | ||||
| Textile/clothing | ||||
| Record-keeping | ||||
| Teaching | ||||
| [Other critical skills] |
Mark “Critical Gap?” as yes if there are zero or one competent practitioners. This makes skill vulnerabilities immediately visible without reading through individual records.
Table 4: Resource Holdings Summary
| Resource | Total | Per Household | Per Person |
|---|---|---|---|
| Arable land (hectares) | |||
| Draft animals | |||
| Livestock (total) | |||
| Grain stores (kg) | |||
| Days of grain reserves | |||
| Dwellings (rooms/units) |
This table connects census data to resource planning. “Days of grain reserves” is a calculated field: current grain stores divided by daily community consumption (itself derived from the population summary table).
Formatting for Clarity and Durability
Summary tables are physical documents in a low-tech community. They will be read in poor light, handled by people with varying literacy, and must remain legible for months or years.
Design guidelines for physical summary tables:
- Use ruled lines between rows. Without ruled lines, the eye loses track of which data belongs to which category across a wide table.
- Use consistent units. Don’t mix “people” with “households” with “percent” in the same column without clear labeling.
- Label every column and every row explicitly. A table that requires a separate key to interpret is too complex. Every cell should be self-explanatory.
- Include the census date prominently. A summary table without a date is worse than useless — it may be mistaken for current data when it is historical.
- Include the recorder’s name. The person who produced the table is accountable for its accuracy and is the person to contact with questions.
Use durable materials. Summary tables that are posted publicly should be written on the most durable available medium — bark, treated leather, heavy cloth — not paper that will disintegrate in humidity. Tables that are archived with the census records can be less durable, but should be stored flat and dry.
Time-Series Comparison Tables
A single census produces a snapshot. Two or more censuses in the same format produce trend data. A time-series comparison table — the same table columns across two or three census periods — reveals demographic change.
| Category | Year 1 | Year 2 | Year 3 | Change Y1→Y3 |
|---|---|---|---|---|
| Total population | 187 | 204 | 198 | +11 / +5.9% |
| Children under 5 | 22 | 28 | 31 | +9 / +40% |
| Adults 15–59 | 121 | 130 | 122 | +1 / +0.8% |
| Dependency ratio | 0.55 | 0.57 | 0.62 | +0.07 |
The example above shows a community growing slightly in total population but with a rising dependency ratio as young children increase. The governance implication: increased investment in childcare and food provisioning for young children is needed, while the productive labor base is only marginally larger. This pattern would not be obvious from a single census snapshot but is immediately visible in the time-series comparison.
Maintain the time-series by appending each new census summary to the same document rather than creating separate documents for each census. After ten years, a community that has been consistent in its census format will have a remarkable record of its own demographic history — a resource for planning, for governance, and for understanding where the community has come from and where it is headed.