The race condition in the original code occurs because multiple threads can access and modify the shared dictionaries (`self.jobs` and `self.results`) without synchronization. Specifically:
1.  **Double Processing:** Two threads could check `if job_id not in self.jobs` at the same time, both see the job exists, and both proceed to process it.
2.  **Data Corruption/Overwriting:** Multiple threads could write to `self.results` simultaneously, potentially overwriting each other's results or causing dictionary integrity issues.

To fix this, we need to use a `threading.Lock` to ensure that only one thread can access or modify these shared resources at a time.

Here is the complete fixed implementation:

```python
import threading

class JobQueue:
    def __init__(self):
        self.jobs = {}
        self.results = {}
        # Initialize a lock to protect shared state
        self.lock = threading.Lock()

    def add_job(self, job_id, data):
        # Lock the dictionary while adding a job
        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
            
            # Retrieve the data and remove it from the queue immediately.
            # We must do this while holding the lock to prevent another thread
            # from picking up the same job (race condition).
            data = self.jobs.pop(job_id)
        
        # Perform the processing outside the lock.
        # This allows other threads to pick up different jobs while this one runs.
        result = processor(data)
        
        with self.lock:
            # Lock again before writing the result to the shared dictionary
            self.results[job_id] = result
            
        return True

    def get_result(self, job_id):
        # Lock the dictionary while reading the result
        with self.lock:
            return self.results.get(job_id)
```

### Key Changes Made:
1.  **Added `self.lock = threading.Lock()`**: Created a synchronization primitive in the constructor.
2.  **Protected `add_job`**: Wrapped the dictionary assignment in `with self.lock:` to ensure jobs are added safely.
3.  **Protected `process_job`**:
    *   Used the lock to check for the job's existence and **remove it** (using `pop`) from `self.jobs`. Removing it immediately prevents multiple threads from processing the same job ID.
    *   Performed the actual `processor(data)` call **outside** the lock. This is crucial for performance; holding the lock during processing would serialize all jobs, defeating the purpose of a concurrent queue.
    *   Re-acquired the lock to write the result to `self.results`.
4.  **Protected `get_result`**: Wrapped the dictionary read in a lock to ensure consistent reads.