Methodology
How People & Consent’s figures were produced
The counts and rates on this page that describe the register, the placement of proposals and the checks are read from the data the instrument publishes, so they change whenever the data does. The worked examples from the Census and the legal citations are stated as fixed facts about those sources. The data was last rebuilt on 2026-10-28.
What the instrument does
The instrument takes one proposal from India’s environmental clearance register and assembles the public record about the place where it would be built. It asks who lives there and what the law requires of a project in that place, a question about one site that needs no comparison between districts, so the instrument gives no score or ranking and applies no weights.
It holds 93,000 proposals, at every stage from filing to decision. A further 26,140 records are left out because the portal has delisted them. They carry no decision and appear in no count on this site.
Establishing where a project is
Every population figure on a profile depends on where the project is placed, so this section sets out the method in detail.
The finest location the register’s search API returns is a project’s state. It has no district field, so the district is read from the application form each proponent files.
That form, the Common Application Form, records the location the proponent declared, with district, sub-district, village and plot numbers. Reading it directly places 99.7% of proposals in a district, and 94.96% in a sub-district as well. The confidence given to each route in the table reflects how specific the statement it rests on is: a named village or sub-district is the most specific, a district named alone is less so, and a district inferred from the project name is the least.
| Route | Proposals | Share | Confidence |
|---|---|---|---|
| Village named in the filing | 71,818 | 77.2% | high |
| Sub-district named in the filing | 16,546 | 17.8% | high |
| District named in the filing | 2,032 | 2.2% | medium |
| Declared district and site coordinates, overruling the place codes | 128 | 0.1% | high |
| A town spanning districts, settled by the site coordinates or declared district | 2,137 | 2.3% | high |
| Inferred from the project name | 56 | 0.1% | low |
| Not determined | 283 | 0.3% | not applicable |
Two features of the form produce answers that look plausible and are wrong, which makes them harder to catch than an outright failure.
The wrong district field. A Common Application Form carries three districts: the project’s, the proponent’s registered office, and the applicant’s address. The last two are often a large city hundreds of kilometres from the site, so only the project’s district is used here.
Two code systems in one record. Within a single filing the village and sub-district codes are Census 2011 identifiers while the district code is a Local Government Directory code. The two numbering systems differ, and treating them as one would join every record to the wrong place. The village code is preferred throughout because it is a Census identifier, and so it resolves correctly even for districts created after 2011. Morbi, created in 2013, resolves through its Morvi sub-district to its 2011 parent, Rajkot, with no table of district changes needed.
1,815 proposals name sites in more than one district, and most of them are linear projects such as highways, transmission lines and pipelines. Their profile describes the primary district, the one named by the most plots unless the reconciliation described next moves it, and states that the project spans other districts too.
Three statements of place, reconciled. A filing states where a project is in three ways: the place codes on its plots, the district it declares and the coordinates of its site. The codes are preferred because they are the most specific, but a code can be wrong in a way the other two reveal. Where the declared district and the coordinates agree with each other against the codes, they decide, and 128 proposals are placed that way. A town that spans more than one district, such as Greater Mumbai or Greater Hyderabad, carries one code for all of them, so the code alone cannot say which district a site is in. Where such a code was the only basis for a placement, the coordinates or the declared district decide (2,135 proposals), and where neither can, the placement is published as provisional. Where no two of the three statements agree (24 proposals), the proposal stays where its codes put it and its page describes the location as contested. Each profile states which of these routes it rests on.
The population record
Socio-economic figures come from the Census of India 2011, obtained through SHRUG, and are added up from sub-district rows to the level being shown. The instrument profiles 640 districts and 5,899 sub-districts.
Census 2011 is 15 years old, but it remains the most recent census for which complete sub-district figures exist. Census 2027 is under way, with its population count scheduled for February 2027, and none of its figures are published yet. Each figure on the profiles states the year of its source beside it.
Every measure, and what it means
Each measure’s definition, the formula that produces it, its source and the year of that source are kept in one registry, and the district files carry only the values. The interface joins the two when it draws a figure, which is how every number on the instrument can show where it came from.
The same design guards against one kind of error. A benchmark and the value it is compared with must resolve to the same registry entry, so a rate is only ever compared with a benchmark computed over the same denominator. Where that check fails, the comparison is left out.
Population
- Total populationpop.total
Everyone enumerated in Census 2011 within the district's 2011 boundary.
sum(pc11_pca_tot_p) over the district's subdistricts
Census of India 2011, Primary Census Abstract, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
- Householdspop.households
Normal households enumerated in Census 2011, the Census term for people who usually live together and eat from a common kitchen.
sum(pc11_pca_no_hh)
Census of India 2011, Primary Census Abstract, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
- Average household sizepop.avg_household_size
People per household, found by dividing the total population by the number of households.
pop.total / pop.households
Census of India 2011, Primary Census Abstract, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
- Scheduled Tribe share of populationpop.st_share
People enumerated as members of a Scheduled Tribe, as a percentage of the whole population, children under seven included.
100 * sum(pc11_pca_p_st) / sum(pc11_pca_tot_p)
Census of India 2011, Primary Census Abstract, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
- Scheduled Tribe is a constitutional status given to communities. Scheduled Areas are declared separately, by Presidential Order under the Fifth Schedule, and many districts with a large tribal population lie outside them, so this share describes who lives here and settles no legal question.
- Scheduled Caste share of populationpop.sc_share
People enumerated as members of a Scheduled Caste, as a percentage of the whole population.
100 * sum(pc11_pca_p_sc) / sum(pc11_pca_tot_p)
Census of India 2011, Primary Census Abstract, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
- Children aged 0-6pop.child_share
Children aged 0 to 6 as a percentage of the whole population.
100 * sum(pc11_pca_p_06) / sum(pc11_pca_tot_p)
Census of India 2011, Primary Census Abstract, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
- Literacy ratepop.literacy_rate
People who can both read and write with understanding in any language, as a percentage of the population aged seven and above. This is the Census of India definition. Measured over the whole population, children included, the rate comes out markedly lower and matches no published Census figure.
100 * sum(pc11_pca_p_lit) / (sum(pc11_pca_tot_p) - sum(pc11_pca_p_06))
Census of India 2011, Primary Census Abstract, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
- Population aged 7 and abovepop.age7plus
The whole population minus children aged 0 to 6, which the Census uses as the base for its literacy rate.
sum(pc11_pca_tot_p) - sum(pc11_pca_p_06)
Census of India 2011, Primary Census Abstract, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
- Sex ratiopop.sex_ratio
Females per 1,000 males, the convention used by the Census of India.
1000 * sum(pc11_pca_tot_f) / sum(pc11_pca_tot_m)
Census of India 2011, Primary Census Abstract, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
Work and livelihood
- Total workerswork.total_workers
Everyone recorded in Census 2011 as a main or marginal worker. A main worker worked for six months or more of the year before the count, and a marginal worker for less than six months.
sum(pc11_pca_tot_work_p)
Census of India 2011, Primary Census Abstract, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
- Work participation ratework.participation_rate
Total workers as a percentage of the whole population, children included, which is the Census of India definition. A labour-force participation rate, computed over the working-age population, is a different measure and runs higher.
100 * sum(pc11_pca_tot_work_p) / sum(pc11_pca_tot_p)
Census of India 2011, Primary Census Abstract, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
- Workers dependent on landwork.land_dependent_share
Cultivators and agricultural labourers, main and marginal together, as a percentage of all workers. These are the workers who earn their living directly from land, and so the people a land acquisition affects most directly.
100 * (main_cl_p + main_al_p + marg_cl_p + marg_al_p) / tot_work_p
Census of India 2011, Primary Census Abstract, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
- The figure counts individual workers. People who live on forest produce or common land are included only if the Census recorded them as cultivators or agricultural labourers.
- Cultivatorswork.cultivator_share
Cultivators, main and marginal, as a percentage of all workers. The Census counts as a cultivator anyone who farms land they own or hold from the government, a private person or an institution.
100 * (main_cl_p + marg_cl_p) / tot_work_p
Census of India 2011, Primary Census Abstract, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
- Agricultural labourerswork.ag_labourer_share
Agricultural labourers, main and marginal, as a percentage of all workers. An agricultural labourer works on another person's land for wages in money, kind or share and holds no right in it, so receives no compensation for the land when it is acquired. Where the 2013 land acquisition Act (RFCTLARR) governs, a labourer who worked in the affected area for the three years before the acquisition, and whose main livelihood it affects, counts as an affected family under section 3(c) and is owed rehabilitation and resettlement.
100 * (main_al_p + marg_al_p) / tot_work_p
Census of India 2011, Primary Census Abstract, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
- Marginal workerswork.marginal_share
Workers who worked for less than six months of the year before the count, as a percentage of all workers. A high share points to seasonal or insecure work.
100 * sum(pc11_pca_margwork_p) / sum(pc11_pca_tot_work_p)
Census of India 2011, Primary Census Abstract, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
- Household industry workerswork.household_industry_share
Workers in household industry, main and marginal, as a percentage of all workers.
100 * (main_hh_p + marg_hh_p) / tot_work_p
Census of India 2011, Primary Census Abstract, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
Village facilities
- Primary Health Centre doctor posts sanctionedinfra.phc_doctors_sanctioned
Doctor positions sanctioned at Primary Health Centres in the district's rural areas.
sum(pc11_vd_ph_cntr_doc_tot)
Census of India 2011, Village Directory, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
- Primary Health Centre doctor posts filledinfra.phc_doctors_in_post
Doctor posts filled at Primary Health Centres in the district's rural areas.
sum(pc11_vd_ph_cntr_doc_pos)
Census of India 2011, Village Directory, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
- Primary Health Centre doctor vacancyinfra.phc_doctor_vacancy_rate
Sanctioned doctor posts left vacant, as a percentage of all sanctioned posts. Both figures come from the same Village Directory columns, so the rate avoids the unit problems that make the directory's raw facility counts unusable.
100 * (doc_tot - doc_pos) / doc_tot
Census of India 2011, Village Directory, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
- The figure covers rural areas only. A district with no sanctioned posts shows no figure.
- In 21 districts the source records more doctors in post than posts sanctioned. We read that as an inconsistency within the Village Directory, so we withhold the rate for those districts and still show both counts.
- Hospitalsinfra.hospitals
All hospitals recorded in the Village Directory for the district's rural areas.
sum(pc11_vd_all_hosp)
Census of India 2011, Village Directory, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
- The figure covers rural areas only, and hospitals in towns and cities are left out.
- Government primary schoolsinfra.primary_schools_gov
Government primary schools in the district's rural areas.
sum(pc11_vd_p_sch_gov)
Census of India 2011, Village Directory, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
- Government middle schoolsinfra.middle_schools_gov
Government middle schools in the district's rural areas.
sum(pc11_vd_m_sch_gov)
Census of India 2011, Village Directory, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
- Some states have no separate middle-school category. All 26 of Gujarat's districts report zero, because its primary schools run to standard 8 and leave no separate middle school to count. Where a measure is zero across a whole state we withhold it, because a zero would suggest the schools are missing.
- Government secondary schoolsinfra.secondary_schools_gov
Government secondary schools in the district's rural areas.
sum(pc11_vd_s_sch_gov)
Census of India 2011, Village Directory, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
Household circumstances
- Rural households (SECC)secc.households
Rural households enumerated in the Socio Economic and Caste Census 2011 and matched to this area in SHRUG.
sum(secc_hh)
Socio Economic and Caste Census 2011, rural households, Ministry of Rural Development, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
- Rural households owning landsecc.land_owning_share
Share of rural households that own land, as recorded in SECC 2011. The table covers rural households only.
100 * sum(land_own_share * secc_hh) / sum(secc_hh), over sub-districts reporting it
Socio Economic and Caste Census 2011, rural households, Ministry of Rural Development, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
- Rural households whose highest earner makes over ₹5,000 a monthsecc.earner_over_5k_share
Share of rural households whose highest-earning member makes more than ₹5,000 a month, as recorded in SECC 2011. Its complement, the share whose highest earner makes ₹5,000 or less, is the form in which SECC deprivation is most often quoted.
100 * sum(inc_5k_plus_share * secc_hh) / sum(secc_hh), over sub-districts reporting it
Socio Economic and Caste Census 2011, rural households, Ministry of Rural Development, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
- Rural households living mainly on manual casual laboursecc.manual_labour_share
Share of rural households whose main source of income is manual casual labour, as recorded in SECC 2011.
100 * sum(inc_source_manlab_share * secc_hh) / sum(secc_hh), over sub-districts reporting it
Socio Economic and Caste Census 2011, rural households, Ministry of Rural Development, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
- Rural households with a salaried membersecc.salaried_share
Share of rural households with any member in salaried employment (government, public or private sector), as recorded in SECC 2011.
100 * sum(salary_any_share * secc_hh) / sum(secc_hh), over sub-districts reporting it
Socio Economic and Caste Census 2011, rural households, Ministry of Rural Development, as compiled in SHRUG v5.0, the Development Data Lab's sub-district dataset for India · 2011
What was deliberately excluded
Several fields in the source look usable and turn out to be unreliable. They are left out, and the reason for each is recorded here.
- Primary Health Centre counts. The Village Directory column sums to roughly 58,800 nationally against about 24,000 actual centres in 2011, with 30,000 in a single sub-district, which shows the column is corrupt at this level of aggregation. The doctor vacancy rate, a ratio of two columns from the same family, is used instead because the ratio holds up whatever unit the counts were recorded in.
- Electricity, water and bus coverage. At sub-district level these are yes-or-no flags recording whether any village has the service, and 5,590 of 5,834 sub-districts read 1. With 96% answering yes nationally, the flag says nothing about how many people are covered, so it is left off the profiles.
- Counts that are zero across an entire state. Every one of Gujarat’s 26 districts reports zero government middle schools while Jamnagar alone reports 1,217 primary schools. Gujarat’s primary schools run to standard 8, so the state has no separate middle schools to count. Where a count is zero across a whole state but substantial nationally, the value is withheld, because a zero would tell readers that the schools do not exist.
- Doctor vacancy where the source contradicts itself. In some districts the Village Directory records more doctors in post than posts sanctioned, which yields impossible rates such as −466%. The rate is withheld in those districts and both raw counts remain visible.
The legal reference, and its limits
Each entry on statutes and standards was transcribed by hand from the provision it cites and checked against the primary source, and each stands independently of the population data. The reference holds 15 obligations, all 15 of them verified against a primary source, and was last reviewed on 2026-09-25.
Whether a place lies in a Scheduled Area under the Fifth Schedule is decided by Presidential Order under paragraph 6 of that Schedule. No authoritative list exists in machine-readable form. When checked in August 2026, the Ministry of Tribal Affairs page that once carried one returned an error (HTTP 404), and the Ministry of Panchayati Raj’s state-wise page gives no Order citations and leaves its coverage columns empty. The Orders themselves were therefore read.
| Scheduled Area status | Districts |
|---|---|
| Named in an Order as wholly scheduled | 39 |
| Named in an Order, but only in part | 67 |
| Outside every Order, which is itself a determination | 533 |
| Not determined | 1 |
639 of the 640 districts have a determined status, reached in one of four ways. A district an Order names takes its status from that Order. Where an Order covers the State but omits the district, the omission settles it, because the Order lists every Scheduled Area in its State. Where no Presidential Order reaches the State, the district lies outside any Scheduled Area. In Assam, Meghalaya, Tripura and Mizoram, Article 244(1) settles the matter, because it applies the Fifth Schedule to Scheduled Areas in every State other than those four. The remaining 1 district is published as not determined, for the reason given below.
Districts drawn after an Order. Every Order defines its area by the territorial divisions that existed on its date, and drawing a new district later leaves the scheduled ground unchanged. A later district’s status therefore follows from where its ground lay on that date. A district carved wholly from one the Order names in whole is wholly scheduled, as are Rayagada, Malkangiri and Nabarangapur, carved from Koraput, and Bijapur, Narayanpur, Alirajpur and Khunti. A district that takes in part of an area the Order names is partly scheduled, and one that takes in none of it is outside. Each such result is checked against the Ministry of Panchayati Raj’s list of notified Fifth Schedule Areas, which names every district decided to be inside and none decided to be outside.
Andhra Pradesh and Telangana are governed by the 1950 Orders C.O. 9 and C.O. 26, which schedule the agency tracts of the old Madras districts and villages of the old Hyderabad State, district by district. The districts they reach are partly scheduled: East Godavari, West Godavari, Visakhapatnam, Srikakulam and Vizianagaram in Andhra Pradesh, and Adilabad, Warangal, Khammam and Mahbubnagar in Telangana. The rest of both States is outside. The text of C.O. 9, the Andhra Pradesh High Court’s list of the agency districts and the Ministry of Panchayati Raj’s list all name the same set.
One district remains undetermined because two official sources conflict over it: the Order does not name it, while the Ministry of Panchayati Raj lists it. The note on each such district’s page cites both. In a partly scheduled district, a site is placed inside the Scheduled Area when its filing puts it in a sub-division the Order names in whole. In every other case the district’s status cannot settle the question, and the page says so.
Two claims that circulate widely are corrected here. C.O. 192 of 2003 is titled for Chhattisgarh, Jharkhand and Madhya Pradesh, and its schedule lists thirty areas in Chhattisgarh and Madhya Pradesh, while Jharkhand’s areas are scheduled by C.O. 229 of 2007. Odisha lies outside C.O. 192 and remains under C.O. 109 of 1977. Rajasthan’s C.O. 114 of 1981 was expressly rescinded by C.O. 270 of 2018, although the Ministry of Tribal Affairs’ own compendium, compiled before 2018, still lists the 1981 Order as operative.
Sixth Schedule areas in Assam, Meghalaya, Tripura and Mizoram fall under a separate constitutional regime, administered through Autonomous District Councils, and the Panchayats (Extension to Scheduled Areas) Act, 1996 (PESA) does not apply to them. They carry their own label, distinct from both scheduled and unscheduled.
Verification
The location is checked against a second document. Everything on this instrument depends on knowing where each project is, and that knowledge comes from a single source, the form the proponent filled in. The placement is therefore tested against the regulator’s signed clearance letter, a separate document written by a different party, which describes the site in prose.
On a random sample of 150 proposals, the district this instrument reports matched the district named in the letter in 86.15% of the 65 cases where the letter could be read and named one. Of the remaining 85, 11 name no district this check could match, and 74 could not be retrieved or read. Those failures reflect the limits of the check itself, and they say nothing about the letters.
Only the text near a location cue in the letter is read. A letterhead carries the issuing authority’s own address, such as Gandhinagar, Bangalore or Chennai, and reading the whole letter would mistake that city for the site.
The site coordinates check every location. Each filing’s mapped blocks are tested against the Census 2011 district boundaries: 89,313 fall inside a district the proposal is placed in and 1,910 on its edge; 928 fall elsewhere, and each of those pages says where the coordinates fall and which statements of place the profile follows instead.
A rebuild that fails its checks publishes nothing. Every measure declares the range it can plausibly fall in, and a value outside that range stops the rebuild. Figures that must add up are checked, so the cultivator and agricultural labourer shares have to sum to the land-dependent share. A sample of the published figures is also worked out a second time from the original sub-district records by a separate calculation, which catches a mistake in the first.
The most recent rebuild recorded 0 failed checks and 0 figures the second calculation could not reproduce. As a test of the whole chain, national literacy worked out from these figures is 72.98% against the Census of India’s published 72.98%. The match is consistent with a literacy denominator of the population aged 7 and above, which is the Census definition; computed over the total population, the rate would be materially lower.
Time to decision and the change log
The time a proposal took to be decided is measured from the first step in its appraisal history, the dated record of steps the portal keeps for each proposal, to the step at which the authority granted or refused what was applied for. The register’s own submission date is published beside it but never measured from, because it moves forward whenever a proposal is submitted again. Days on which the portal had a proposal automatically delisted are subtracted and published separately, so the first filing date plus the days to decision plus the days delisted equals the decision date on every decided proposal.
The source timestamps are in UTC and are converted to India Standard Time before a date is taken. The change log dates each event by the same history: a filing or a decision by the end of its step, and a query, closure or other step by its start. Each event also records the build in which it first appeared, so a reader following the log can ask for everything that is new since a previous visit, including steps the portal recorded late.
Limits of the evidence
- 283 proposals could not be placed in any district. For 1 of them the Ministry’s portal serves no Common Application Form at all, and 0 have not been read yet. The rest were read and record no village, sub-district or district, and their project names contain no district that matches the Census gazetteer. They are reported as undetermined, and their profiles show no state averages in place of district figures.
- The record of whether the Forest Rights Act was complied with before forest land was diverted lies outside the public data. That certificate is part of the forest clearance application completed by the District Collector, and the portal serves that part only to signed-in users. The instrument shows the public part instead: the forest proposal the environmental form names and its current stage in the forest register.
- Counts of affected and displaced families are the figures each proponent declared in its application. They are the proponent’s own statements, and the pages label them as declared wherever they appear.
- Whether a place lies within a Scheduled Area under the Fifth Schedule is a legal determination made by Presidential Order, and no authoritative list exists in machine-readable form. Where the transcribed Orders do not settle a place, the instrument reports its status as not determined. It never infers the status from the share of Scheduled Tribes in the population, because a Scheduled Area exists only where an Order creates one, and a place’s tribal share does not decide whether it does.
- The register as this instrument reads it begins with proposals submitted in September 2022, so it covers only the recent part of the history of environmental clearance in India.
- Population figures are shown for the sub-district or district even where a village is named. The village identifies the place, and the profile then reports the record for the sub-district or district, the level at which the Census measures used here are published.
Sources
- PARIVESH environmental clearance registerMinistry of Environment, Forest and Climate ChangeUpdating source · read 28 October 2026proposals submitted 2022 onward
- PARIVESH Common Application FormMinistry of Environment, Forest and Climate ChangeUpdating source · read 28 October 2026project location as filed by the proponent: district, sub-district and village, plus declared land area, affected and displaced families
- Census 2011 Primary Census AbstractOffice of the Registrar General of India, via SHRUGCollected 2011 · version 5.0
- Census 2011 Village DirectoryOffice of the Registrar General of India, via SHRUGCollected 2011 · version 5.0
- Socio Economic and Caste Census 2011, ruralMinistry of Rural Development, via SHRUGCollected 2011 · version 5.0rural households only: land ownership, income band, main source of income and salaried employment
- PARIVESH appraisal historyMinistry of Environment, Forest and Climate ChangeUpdating source · read 28 October 2026every dated step a proposal has passed through, from submission to decision. Individual officers are named in the source and are not recorded here.
- Census 2011 district boundariesdatameetCollected 2011district outlines as they stood at the 2011 Census, used to test filed coordinates against the district a proposal names
Everything here is produced by one process that can be run again from the same sources. Each run records the match rate for every placement route it used and every check that failed.