Here's the corrected implementation of the `JobQueue` class with proper concurrency control using a `threading.Lock`. This ensures thread-safe access to shared resources (`self.jobs` and `self.results`) across all methods that modify or read them.

```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]
            result = processor(data)
            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)
```

### Key Fixes:

- **Added a `threading.Lock`** to synchronize access to shared state (`self.jobs`, `self.results`).
- **Protected all dictionary operations** (`add`, `get`, `delete`) with the lock to prevent race conditions.
- **Ensured atomicity** of read-modify-write sequences inside `process_job`.
- **No additional state** (like `self.pending`) is needed since the lock enforces safe access.

This implementation guarantees that all operations on the job queue are thread-safe, eliminating the original concurrency bug.