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From the IFT source library

Critical Crime-Data Principle

Topic-specific explanations and research proposals developed from IFT source content. Local evidence, permissions, costs and results remain to be established.

Original source ↗

Understand the topic

What this means in daily life

Crime records show what was reported, registered and recorded; they are not a direct count of every harmful event. This topic asks readers to examine reporting access and other evidence before interpreting a falling or rising number.

A rise in recorded cases can reflect more harm, improved access to reporting, changed recording practices or several changes together. The interpretation should state which explanations the available evidence supports and which remain unresolved.

Data reference table

Evidence Snapshot

Read each value with its reporting period, population and limitations. A historical national reference is not a local baseline or proof that an IFT proposal works.

5 measurement records still need data and a review of their relevance.

Data references for Critical Crime-Data Principle
SignalReference ValuePeriod / PopulationHow to Read ItSource Status
Indicators with complete metadata

Not established

Data required — not zero

Reporting period: Information Required

Population and geography: Information Required

Proposed measure; no observed value is established here.

Limitations: Define the measure, unit, reporting period and covered population; obtain a traceable dataset and review its suitability for this topic before using a number.

Source organisation: Information Required

Direct source URL: not yet verified

Source publication date: not established

Verification status: Data required

Reporting/health/survey triangulation

Not established

Data required — not zero

Reporting period: Information Required

Population and geography: Information Required

Proposed measure; no observed value is established here.

Limitations: Define the measure, unit, reporting period and covered population; obtain a traceable dataset and review its suitability for this topic before using a number.

Source organisation: Information Required

Direct source URL: not yet verified

Source publication date: not established

Verification status: Data required

Correction turnaround

Not established

Data required — not zero

Reporting period: Information Required

Population and geography: Information Required

Proposed measure; no observed value is established here.

Limitations: Define the measure, unit, reporting period and covered population; obtain a traceable dataset and review its suitability for this topic before using a number.

Source organisation: Information Required

Direct source URL: not yet verified

Source publication date: not established

Verification status: Data required

Privacy incidents

Not established

Data required — not zero

Reporting period: Information Required

Population and geography: Information Required

Proposed measure; no observed value is established here.

Limitations: Define the measure, unit, reporting period and covered population; obtain a traceable dataset and review its suitability for this topic before using a number.

Source organisation: Information Required

Direct source URL: not yet verified

Source publication date: not established

Verification status: Data required

Projects completing women-impact review

Not established

Data required — not zero

Reporting period: Information Required

Population and geography: Information Required

Proposed measure; no observed value is established here.

Limitations: Define the measure, unit, reporting period and covered population; obtain a traceable dataset and review its suitability for this topic before using a number.

Source organisation: Information Required

Direct source URL: not yet verified

Source publication date: not established

Verification status: Data required

Different surveys, administrative records, estimates and reporting years are not interchangeable. No combined IFT score is calculated from these rows.

10 ideas for this topic

What could be done — and what needs testing

These are proposals for research and local testing. They are not claims that a project has been funded, implemented or proved successful.

Idea 01

Recorded-unit dictionary

Explain whether a published count represents complaints, incidents, registered cases, people or service contacts.

What to check: Define whether the unit is a report registered case person or event

Idea 02

Reporting-access comparison

Study whether travel, language, disability or fear changes the ability to reach a reporting service.

What to check: Document changes in reporting access

Idea 03

Registration-practice review

Ask authorised reviewers whether recording procedures changed during the period being compared.

What to check: Separate registration practice from incident interpretation

Idea 04

Multiple-source comparison

Compare relevant police, health and survey evidence while explaining that they measure different things.

What to check: Compare suitable independent sources and explain differing coverage

Idea 05

Missing-data display

Show unavailable periods or areas explicitly rather than treating an empty cell as zero incidents.

What to check: Show missing values without treating them as zero

Idea 06

Boundary-change note

Explain when jurisdiction, category or population changes make a trend difficult to compare.

What to check: Explain changed boundaries and population denominators

Idea 07

Confidential experience research

Use qualified researchers and safe methods to understand barriers that administrative records cannot show.

What to check: Use ethical voluntary methods and protect confidential experience

Idea 08

No-target suppression check

Examine whether performance targets encourage non-registration, reclassification or pressure not to complain.

What to check: Check whether performance targets discourage registration

Idea 09

Public interpretation examples

Show how the same reported count can have several plausible explanations requiring further evidence.

What to check: Test whether examples explain competing interpretations honestly

Idea 10

Correction history

Keep a dated record of revised definitions, corrected values and the effect on earlier conclusions.

What to check: Preserve dated corrections and revise affected comparisons

15 questions, answered clearly

Questions about Critical Crime-Data Principle

Do fewer FIRs prove less crime?

No. Reporting access and recording practices affect totals

Can higher reports reflect progress?

Better access or trust may increase recorded concerns

Is a survey a complete measure?

No. Design, recall, coverage and willingness to respond affect findings

Why consult health evidence?

It may illuminate needs absent from police records, with important limitations

Can raw district counts be ranked directly?

Population, definitions and coverage need alignment

What does zero recorded incidents mean?

It shows no incidents in that record, not necessarily no harm

Why disclose reference periods?

Different time windows can create misleading comparisons

Should subgroup data always be public?

No. Privacy and statistical reliability constrain useful detail

Can combined sources remove all uncertainty?

No. Their gaps and different purposes remain relevant

What is a responsible conclusion?

One proportionate to the available evidence and explicit about reporting context

What would the “Boundary-change note” idea involve?

Explain when jurisdiction, category or population changes make a trend difficult to compare. What to check: Explain changed boundaries and population denominators

What would the “Confidential experience research” idea involve?

Use qualified researchers and safe methods to understand barriers that administrative records cannot show. What to check: Use ethical voluntary methods and protect confidential experience

What would the “No-target suppression check” idea involve?

Examine whether performance targets encourage non-registration, reclassification or pressure not to complain. What to check: Check whether performance targets discourage registration

What would the “Public interpretation examples” idea involve?

Show how the same reported count can have several plausible explanations requiring further evidence. What to check: Test whether examples explain competing interpretations honestly

What would the “Correction history” idea involve?

Keep a dated record of revised definitions, corrected values and the effect on earlier conclusions. What to check: Preserve dated corrections and revise affected comparisons