Here's the corrected implementation of the `JobQueue` class that resolves the race condition using proper locking mechanisms:

```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]
            del 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

        return True

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

### Explanation of the Fix

1. **Added a Lock:** A `threading.Lock` is used to synchronize access to the shared `jobs` and `results` dictionaries.

2. **Protected Critical Sections:**
   - In `add_job`, the lock ensures that adding a job is an atomic operation.
   - In `process_job`, the lock is held while checking and removing the job from the queue, and then while writing the result. This prevents concurrent modifications to these shared structures.
   - In `get_result`, the lock ensures thread-safe access to the `results` dictionary.

3. **Improved Concurrency:**
   - The actual job processing (`processor(data)`) is performed outside the lock. This avoids blocking other threads from accessing or modifying the queue while a long-running task is in progress.

4. **Prevented Race Conditions:**
   - The original code allowed multiple threads to read and write the same data without synchronization. The fix ensures that all accesses to shared state are serialized, eliminating the possibility of data corruption or lost updates.

This implementation is now thread-safe and suitable for use in multi-threaded environments where jobs may be added, processed, and retrieved concurrently.