Understand the topic
What this means in daily life
Digital tools can widen access but also expose women to fraud, harassment or unwanted disclosure. This topic proposes testing actual user journeys and human support before treating automation as a safety solution.
A digital safety feature can itself reveal a help request through a notification, shared account or visible history. Proposed tools need a safe route to human assistance and a practical alternative for people unable to use the technology privately.
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.
| Signal | Reference Value | Period / Population | How to Read It | Source Status |
|---|---|---|---|---|
| Report-to-acknowledgement time | 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 |
| Evidence preservation success | 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 |
| Offline-risk escalation | 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 |
| False-positive/negative rates | 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 |
| Appeal and correction time | 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.
Evidence coverage and review log (CSV) · Structured evidence register (JSON)
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.
Abuse-report journey tests
Use fictional cases to test whether a user can report online abuse and understand the next step.
What to check: Check accessibility and whether the route increases exposure.
Human review for AI flags
Require a qualified reviewer before an automated flag affects a person or case.
What to check: Examine false alerts and missed concerns across user groups.
Private device access
Study how shared phones and accounts affect access to safety services.
What to check: Test whether messages reveal a help request to others.
Account recovery practice
Offer safe practice in recovering a fictional account through official channels.
What to check: Check whether users recognise impersonated support contacts.
Evidence preservation referrals
Direct digital-evidence questions to authorised specialists rather than ask users to investigate offenders.
What to check: Check that reporting does not require unsafe confrontation.
Consent-aware data design
Separate essential service data from optional research or analytics.
What to check: Test whether declining optional use blocks ordinary help.
Language and disability trials
Test interfaces with women who use different languages and access tools.
What to check: Record errors that an average accuracy figure conceals.
Fraud warning library
Explain recurring deceptive messages through fictional examples and verified service routes.
What to check: Assess whether users can identify uncertainty without being blamed.
Vendor accountability terms
Define access controls, deletion, incident reporting and independent scrutiny before procurement.
What to check: Verify what happens when a supplier fails or changes ownership.
Safe offline alternatives
Keep a reachable human or in-person route when digital access fails.
What to check: Compare outcomes for women who cannot use the app.