# The Relocation Likelihood Score for Sourced Candidates

*You will score any sourced candidate's relocation likelihood from public evidence and sort a pool into pursue-now, probe, or skip without unlawful inferences.*

- Canonical URL: https://www.refolk.ai/guides/relocation-likelihood-score
- Pillar: Recruiting and sourcing
- Format: Framework
- Published: 2026-08-24
- Last reviewed: 2026-08-24
- Reading time: 16 min
- Keywords: how to tell if a candidate will relocate, sourcing candidates open to relocation, relocation willingness signals recruiting, screening candidates for onsite role location fit, candidate relocation risk assessment

## Key takeaways

- In Refolk's index, only 40 of 346,160 US Software Engineer profiles carry the phrase 'open to relocation' - about 1 in 8,650 - so the stated flag is useless as a primary filter.
- Stated willingness overstates action by roughly 18x: 44% of US workers say they would relocate, but only 2.4% actually relocated for a job in Q1 2024.
- Renter-versus-owner status is the single most defensible mobility proxy and it is lawful, because it correlates through mortgage lock-in rather than any protected characteristic.
- High compensation predicts relocation better than any stated preference: earners above $200k relocated at 3.7% versus 2.4% overall.
- Relocation acceptance base rates of roughly 2 to 4 percent mean you must size the pool with a multiplier plus a 20 to 30 percent supply cushion or it collapses at offer.
- Never infer mobility or work authorization from a name or perceived national origin; the only lawful question is a uniform 'authorized to work in the US?' asked of everyone identically.

You have a role that must be filled on-site in one city, and a sourced pool that mixes locals, near-locals, and people who would have to move. This guide gives in-house recruiters and sourcers a scored, pre-outreach read on which candidates are worth pursuing, built from public evidence and bounded by explicit guardrails on what you may and may not infer. The output is a defensible pursue-now, probe, or skip call for every name, before you spend a single message.

Most pages on this topic are candidate-facing resume advice or generic HR notes on interview questions. Neither tells a sourcer how to score a stranger's relocation likelihood from what is publicly visible. That is the gap here.

## Why stated relocation preference is the wrong thing to filter on

The "open to relocation" flag is near-useless as a primary filter because almost nobody sets it, and the people who do are as likely to be gaming search visibility as signalling real intent. In Refolk's index of professional profiles, only 40 of 346,160 US profiles titled "Software Engineer" carry the phrase "open to relocation" in their text. That is about 0.012 percent, or roughly 1 in 8,650. Filter on the flag alone and you discard about 99.99 percent of your pool, including nearly everyone who would actually move.

The second problem is coaching. Candidate-facing advice openly tells people to add "open to relocation" to widen the roles they match, so the field signals search strategy as often as genuine willingness. Treat it as a tiebreaker, not a gate.

**1 in 8,650 - US Software Engineer profiles carrying "open to relocation" text**

In Refolk's index, only 40 of 346,160 US Software Engineer profiles use the phrase, so it cannot be a primary filter.

The gap between talk and action is the core screening problem. CareerBuilder found 44 percent of US workers said they would relocate for a career opportunity. Yet a survey of more than 3,000 US workers found only 2.4 percent actually relocated for a job in Q1 2024, up from a record low of 1.5 percent the prior quarter. Willingness overstates action by roughly 18x. A "yes, I'd relocate" is weak evidence on its own, because moving demands housing, capital, and family buy-in that abstract willingness ignores.

| Segment | Total profiles | With "open to relocation" text | Rate (derived) |
|---|---|---|---|
| Software Engineer, US | 346,160 | 40 | 0.012% (~1 in 8,650) |
| Software Engineer, UK | not pulled | 4 | n/a |
| Registered Nurse, US | not pulled | 5 | n/a |

The scarcity holds across markets and functions: 4 UK Software Engineer profiles and 5 US Registered Nurse profiles carry the phrase. Wherever you source, the stated field is too thin to build on. Score on behavior instead.

## The signals that actually predict relocation follow-through

Documented mobility facts, not stated intent, are the load-bearing signals. The four that carry weight are prior cross-region moves, renter-versus-owner status, tenure in the current city, and compensation band. Each proves something specific, and each can lie in a specific way.

**Prior cross-region moves.** Someone who has already picked up and moved states for work has demonstrated the capability and paid the cost once. It is a real base-rate signal, but keep it in proportion: only 19.3 percent of US movers changed states in 2024, down slightly from 20.1 percent in 2023, so long-distance moves are the minority even among movers. It lies when the moves were involuntary. A history of many addresses may reflect a renter lifestyle or military service, not career-driven relocation. Separate involuntary moves from deliberate ones before you score.

**Renter versus owner.** This is the single most defensible mobility proxy, and it is lawful. Renters move far more than owners: across the 100 largest US cities, homeowner mobility fell in 41 cities while renter mobility rose from 2019 to 2024, and the academic consensus is that owners are less likely to move because lower mobility reduces the value of distant job offers. The mechanism is mortgage lock-in and affordability, not any protected trait, which is why it survives the EEOC guardrail that address history is a lawful inquiry. It lies as a veto: an owner in a cheap or high-growth market may move readily, and owner mobility rose in more than a dozen cities. Weight tenure and market, never ownership as an automatic skip.

**Tenure in the current city.** Short time in place points to lower switching cost. Long tenure points to roots and inertia. One in six renters (16.6 percent) stayed in the same home 10 or more years in 2022, up from 13.9 percent a decade earlier, so long tenure is real and rising. It lies for people who are settled by choice but would move for the right role, which is exactly what the confirm question exists to catch.

**Compensation band.** High comp predicts relocation better than any stated preference. Earners above $200k relocated at 3.7 percent versus 2.4 percent overall in Q1 2024. Higher pay offsets moving cost and often comes with a package, so seniority and comp band belong in the score. Age skews too: people aged 25 to 34 (37.25 percent) and 35 to 44 (23.78 percent) were most willing to move, but you infer this from career stage and role level, never by asking or estimating age.

#### Weighting the mobility signals

1. **Stated "open to relocation" text** - Lightest weight; a tiebreaker only, because it is rare and coachable
2. **Compensation band** - Higher pay offsets moving cost; $200k+ earners relocate at 1.5x the base rate
3. **Tenure in current city** - Short tenure lowers switching cost; long tenure signals roots
4. **Renter vs owner** - The most defensible lawful proxy, via mortgage lock-in not protected traits
5. **Prior cross-region moves** - The base; demonstrated capability and paid cost once

*Score from the bottom up, treating documented behavior as the base and stated text as the lightest confirmation.*

> **Watch out:** Address history is not intent
>
> A long list of past addresses can mean a renter lifestyle or military service, not career relocation. Separate involuntary moves from deliberate career moves before you score, or you will read mobility into churn.

## The guardrail: what you may and may not infer

You may screen on job-related location fit and lawful facts, and you may not infer mobility or work authorization from any protected characteristic. This line is not optional and it comes before any scoring.

The frame is verify versus discriminate. IRCA requires employers to verify all workers are eligible to work in the US through the Form I-9, and the same law prohibits discrimination based on real or perceived citizenship or immigration status. The EEOC recommends that pre-employment information be limited to what is essential to determine whether a person is qualified; race, sex, national origin, age, and religion are irrelevant to that.

| Lawful to consider or ask | Unlawful to ask or infer |
|---|---|
| Current and prior addresses | Citizenship status before an offer |
| "Are you authorized to work in the US?" | Birthplace or country of citizenship |
| Prior cross-state moves in work history | Naturalized versus native-born |
| Renter-vs-owner and tenure proxies | Family status, ties, or dependents |

Two rules govern the edges. Work authorization is a lawful, essential inquiry: one essential question is whether an applicant is authorized to work in the United States, and you may pre-screen for who would need sponsorship and condition employment on documentation at the I-9 stage. But documents and citizenship are off-limits pre-offer: under IRCA no employer may ask applicants about citizenship status before a job is offered, including requesting citizenship documentation.

> **Rule:** Never infer from a name
>
> Do not infer work authorization, national origin, or mobility from a name or perceived nationality. The only lawful path is the uniform question "Are you authorized to work in the US?" asked of everyone identically.

## The scoring rubric

Score each candidate 0 to 10 across the four behavioral signals plus the stated flag, then band the total. The bands are pursue-now, probe, and skip, and skip is only ever a low mobility score, never a protected-trait inference.

**Relocation likelihood score (0-10)**

```
+3  Prior cross-region (cross-state) move for work, deliberate
+2  Renter in current city (or owner with under 2 years tenure)
+2  Under 2 years tenure in current city
+2  Comp band at or above senior/specialist level for the role
+1  Explicit "open to relocation" text or target city listed
 0  Owner with long tenure in a locked-in, high-cost market

Band the total:
  7-10  PURSUE NOW  - strong mobility evidence, message first
  4-6   PROBE       - mixed; confirm on phone screen before investing
  0-3   SKIP         - low mobility evidence; deprioritize, do not disqualify on protected grounds
```

*Adjust the point weights to your market. Cheap or high-growth target cities should lower the owner penalty.*

The bands are triage, not verdicts. A pursue-now score means the mobility evidence justifies spending outreach first. A probe score means the evidence is mixed and a confirm question resolves it cheaply. A skip score means you deprioritize, and you re-examine the market assumption rather than the person. Owner status in a high-growth or low-cost city should not sink a score, because owner mobility rose in more than a dozen cities.

#### Where each candidate sits before outreach

Horizontal axis runs from Weak mobility evidence to Strong mobility evidence. Vertical axis runs from Intent unconfirmed to Intent confirmed.

| Quadrant | What it means |
| --- | --- |
| Probe carefully | Weak evidence, no confirmation - deprioritize and re-check the market |
| Probe to confirm | Strong evidence, not yet asked - phone screen with concrete terms |
| Nurture or skip | Weak evidence, said no - park unless the package changes |
| Pursue now | Strong evidence and a confirmed yes - move first |

*Two axes decide the call: documented mobility evidence and confirmed intent.*

I ran this search: `Senior mechanical engineers who have already moved across state lines at least twice and now live within 100 miles of Columbus, Ohio.` - [see the full result list](https://www.refolk.ai/s/wgnqe8v4bw).

*Returns engineers whose public history already shows the behavior the score rewards, pre-filtered to the on-site radius.*

Behavioral queries like that one are how you skip the near-useless flag entirely. Instead of hunting for the 1-in-8,650 who typed the phrase, [Refolk](/) lets you ask for the mobility evidence directly, then you apply the rubric to a pool that is already skewed toward likely movers.

## Reading the platform filters without being fooled

Structured location filters are a useful first cut, but they are self-declared, coachable, and radius-blind, so treat their output as a raw list to be re-scored, not a shortlist. LinkedIn Recruiter exposes relocation as three settings: "Current" includes candidates listing that location, "Open to relocate only" includes those who indicated openness to relocate to your location, and "Current or open to relocate" includes both. Recruiters cross-check the resume address or application location against the field, and discrepancies are a red flag worth probing.

The trap is the radius. There is an implied 100-mile radius on any location selection, so a filtered "local" pool silently includes people up to 100 miles out. For a true on-site role, that is the difference between a commuter and a mover you have miscounted as local. Use a postal-code radius filter for genuine on-site fit.

**2x - Response-rate lift from candidates open to opportunities and relocation**

LinkedIn reports these candidates are twice as likely to respond, which is a reason to prioritize them, not proof they will move.

One structured signal is genuinely worth acting on: candidates who indicate they are open to new opportunities and relocation are twice as likely to respond to a message. That is a response-rate advantage, not a follow-through guarantee. Prioritize them for the phone screen; do not skip the confirm.

## Sizing the pool to the base rate

Relocation acceptance runs roughly 2 to 4 percent, and searches decay with time, so a pool that looks healthy on headcount will collapse at offer unless you multiply it and add a supply cushion. Under-sizing is the quiet killer of on-site searches.

| Anchor | Value |
|---|---|
| Interview-stage drop-off benchmark | 25% |
| Drop-off increase past 40 days | +12% |
| Specialized/senior fill time | 90+ days |
| Suggested supply cushion, tight market | 20-30% |

Work the arithmetic backward from offers. Pool-multiplier logic is well documented in the general case: a 70 percent post-interview drop-off means sourcing 10 candidates to reach 3 at offer, against a company average of 5. Layer the relocation base rate on top. Drop-off jumps 12 percent when hiring stretches past 40 days, and senior or specialized roles routinely run beyond 90 days. Add the recommended 20 to 30 percent cushion when candidate supply is tight in your geography.

| Metric | Value | Ratio to action (derived) |
|---|---|---|
| Would relocate (willing) | 44% | 18.3x the acting rate |
| Relocated Q1 2024 (all) | 2.4% | 1x baseline |
| Relocated Q1 2024 ($200k+) | 3.7% | 1.5x baseline |

A relocation-specific offer-stage acceptance rate is not established publicly, so do not invent one. Size against the general drop-off anchors above and treat the 2 to 4 percent action rate as your reality check on how many likely movers you actually need in the top of the funnel.

> A pipeline that looks healthy on headcount collapses at offer when relocation acceptance runs two to four percent.

## The procedure

This is the seven-step run from a defined role to a defensible shortlist. Steps 1 and 2 are setup, 3 through 5 build and size the scored pool, and 6 and 7 confirm intent and hand off.

#### Score and sort a relocation pool

1. **Define the location requirement precisely** - With the hiring manager, fix the city, the radius, the on-site cadence, and whether a package exists. Done when the JD states the location expectation in one unambiguous line.
2. **Set the guardrail before sourcing** - Write down what you may infer (address history, prior moves, the stated flag, the work-authorization question) and what you may not (citizenship, national origin, family status). Done when your skip criteria contain zero protected characteristics.
3. **Pull the pool with structured filters** - Use platform location and "open to relocate" filters as a first cut, remembering the implied 100-mile radius. Done when you have a raw list tagged by declared location status.
4. **Score each candidate on mobility evidence** - Rate prior cross-region moves, renter-vs-owner proxies, tenure, comp band, and any explicit relocation text. Done when each candidate carries a numeric score and a pursue/probe/skip band.
5. **Size the pool to the base rate** - Apply a multiplier because acceptance runs ~2-4%, then add the 20-30% supply cushion for a tight geography. Done when pool size reflects expected drop-off, not raw headcount.
6. **Probe intent early with confirm questions** - On a 15-30 minute recruiter phone screen, confirm the candidate's own prior statement and present concrete location, timeline, and package. Done when intent, timeline, and package expectation are on record.
7. **Re-band and hand off** - Move confirmed movers to pursue-now and disqualify only on job-related grounds. Done when the shortlist survives a review that asks why each person was cut.

The phone screen carries the decision, so run it right. Because the pre-screen is where a candidate can first weigh a concrete opportunity, pair the confirm question with real details. Without information about the role, relocation logistics, and salary, a candidate cannot give a definitive answer, and a genuine "yes" can read as a hesitant "maybe."

**Relocation confirm question for the phone screen**

```
"Your application indicates you would be open to relocation to any state
 in the US. Is that still true?

 To be concrete: this role is fully on-site in [city], we would want a start
 within [timeline], and [there is / there is not] a relocation package. With
 those specifics, is relocating something you would seriously consider?"
```

*Swap in your city and terms. Ask it identically of every candidate; never follow up about family, ties, or protected traits.*

Sources disagree on order. Some place the relocation confirm in the application form as a deal-breaker question; others put it in the first phone screen. Either works, provided you present concrete terms before you score the answer.

## How this goes wrong

The failure modes below are the most valuable part of the standard, because each is a false positive that survives a careless read. Every one has a check that keeps the call defensible.

- **Trusting the "open to relocation" flag.** The candidate added it purely to surface in more searches, and advice pages coach exactly that. Check: confirm against prior move history and a direct question, never the flag alone.
- **Reading homeownership as a veto.** An owner in a high-growth or cheap market may move readily; owner mobility rose in more than a dozen cities. Check: weight tenure length and market, not ownership per se.
- **Radius blindness.** A filtered "local" pool silently includes people up to 100 miles out. Check: use the postal-code radius filter for true on-site fit.
- **Address-history over-reading.** Many past addresses may reflect a renter lifestyle or military service, not job-relocation intent. Check: separate involuntary moves from career moves before scoring.
- **Inferring from name or nationality.** This is the unlawful trap. Never infer work authorization or mobility from perceived national origin. Check: only the uniform "authorized to work in the US?" question, asked of everyone identically.
- **Confirming intent with no details.** A "maybe" reads as a "no" because the candidate lacked salary, package, and timeline. Check: present concrete relocation terms before you score the answer.
- **Under-sizing the pool.** A pipeline looks healthy but collapses at offer because acceptance runs 2 to 4 percent. Check: multiply against drop-off and add the supply cushion.

> **Tip:** Code relocation as its own decline reason
>
> A recommended decline taxonomy codes "relocation" as a distinct reason category. Log it that way, and over a few searches you build a private base rate for your own market that beats any national average.

## Before you call the shortlist done

Run this check before you hand the pool to the hiring manager. It confirms the score is defensible, the pool is sized, and no cut rests on a protected characteristic.

#### Relocation shortlist readiness

- [ ] The JD states the city, radius, and on-site cadence in one unambiguous line.
- [ ] Every skip criterion is job-related and contains zero protected characteristics.
- [ ] Each candidate carries a numeric mobility score and a pursue/probe/skip band.
- [ ] The "local" pool was filtered by postal-code radius, not just a location name.
- [ ] Pool size reflects the 2-4% acceptance base rate plus a 20-30% supply cushion.
- [ ] Every pursue-now candidate has intent, timeline, and package expectation on record.
- [ ] The work-authorization question, if asked, was worded and applied identically to all.

To keep the model current, log every relocation outcome against its pre-outreach band and re-check three things over time. First, your own accept-versus-decline rate by band, which is the private base rate worth trusting over any national figure. Second, the platform radius behavior, which can change and quietly reshape who counts as local. Third, the renter-versus-owner mobility trend in your target market, because the owner tether weakens in cheap or high-growth cities and strengthens where affordability locks people in. The rubric is a starting weighting; your own data is what makes it defensible.

## Frequently asked questions

### How can I tell if a candidate will relocate before I contact them?

You cannot know for certain, but you can score likelihood from public behavioral evidence. Weight documented facts over stated intent: prior cross-region moves in the work history, renter-versus-owner proxies, short tenure in the current city, and compensation band. Treat any 'open to relocation' text as weak confirmation only, never a primary filter, because willingness overstates action by roughly 18x. The score sorts a pool; a confirm question on the phone screen decides.

### Is it legal to screen sourced candidates for relocation willingness?

Yes, when you screen on job-related location fit and lawful facts. Address history and the question 'Are you authorized to work in the United States?' are lawful pre-employment inquiries. What is unlawful is inferring mobility or work authorization from citizenship, national origin, birthplace, or a name. Under IRCA no employer may ask about citizenship status or request citizenship documents before an offer. Keep every skip criterion job-related and applied to everyone identically.

### Why is the 'open to relocation' profile field so unreliable?

It fails two ways. First, it is vanishingly rare: in Refolk's index only 40 of 346,160 US Software Engineer profiles carry the phrase, about 1 in 8,650, so filtering on it discards nearly your whole pool. Second, candidate-facing advice openly coaches people to add it purely to surface in more searches, so it signals search strategy as often as genuine intent. Use it as a tiebreaker, not a filter.

### What is a realistic relocation acceptance rate to plan against?

Plan against roughly 2 to 4 percent actual relocation. A survey of over 3,000 US workers found 2.4 percent relocated for a job in Q1 2024, rising to 3.7 percent among earners above $200k. A relocation-specific offer-stage acceptance rate is not established publicly, so size the pool with a multiplier against general drop-off and add a 20 to 30 percent supply cushion for a tight geography.

### How should I ask about relocation on a phone screen?

Confirm against the candidate's own prior statement and pair it with concrete terms. A clean model: 'Your application indicates you would be open to relocation to any state in the US. Is that still true?' Then state the city, timeline, and whether a package exists, because without those details a candidate cannot give a definitive answer and a real 'yes' can read as a 'maybe.' Never ask about family, ties, or protected traits.

### Does homeownership mean a candidate will not relocate?

No. Homeownership is a probabilistic tether, not a veto. Owners move less on average because of mortgage lock-in and affordability, but owner mobility rose in more than a dozen cities and the tether weakens in cheaper or high-growth markets. Weight tenure length and local market conditions rather than ownership alone, and never treat an owner as an automatic skip.

---

*From the Refolk guide library. I revise these guides rather than replacing them, so the current version is always at https://www.refolk.ai/guides/relocation-likelihood-score*