Here's the corrected implementation of the `JobQueue` class with proper locking to eliminate the race condition:

```python
import threading

class JobQueue:
    def __init__(self):
        self.jobs = {}
        self.results = {}
        self.lock = threading.Lock()

    def add_job(self, job_id, data):
        with self.lock:
            self.jobs[job_id] = data
        return job_id

    def process_job(self, job_id, processor):
        with self.lock:
            if job_id not in self.jobs:
                return False
            data = self.jobs[job_id]

        # Process job outside the lock to avoid blocking other threads
        result = processor(data)

        with self.lock:
            self.results[job_id] = result
            del self.jobs[job_id]

        return True

    def get_result(self, job_id):
        with self.lock:
            return self.results.get(job_id)
```

### Explanation of the Fix

1. **Thread-Safe Access:**
   - A `threading.Lock()` is introduced to synchronize access to shared state (`self.jobs` and `self.results`).

2. **Atomic Operations:**
   - In `process_job`, the check for job existence and retrieval of job data are performed within the lock to ensure they are atomic.
   - Writing results and deleting the job are also done under the lock to maintain consistency.

3. **Avoid Blocking During Processing:**
   - The processor function is executed outside the lock to prevent blocking other threads while the job is being processed.

4. **Thread Safety for All Public Methods:**
   - `add_job`, `process_job`, and `get_result` all use the lock to protect their respective operations on shared data structures.

This implementation ensures that concurrent access to the job queue does not lead to race conditions or data corruption.