## Step 1: Define the symbolic representation of the variables
The variables are 'hours worked by Hank', 'hours worked by Laura', 'hours worked by Bobby', and 'hours worked by George'. Let's denote them as $x_1$, $x_2$, $x_3$, and $x_4$ respectively.

## Step 2: Convert the objective function into a symbolic representation
The objective function to maximize is $1.49x_1 + 2.46x_2 + 7.06x_3 + 6.37x_4$.

## Step 3: List all the constraints in symbolic notation
1. $2x_1 \geq 2$ is not correct, $x_1$ has an organization score of 2, which implies $2x_1 = 2$ but for the model we consider $2x_1 \geq 2$ and $2x_1 \leq 2$ or simply $x_1 \geq 1$ and $x_1 \leq 1$ but we actually use $2x_1 = 2$ or $x_1 = 1$ as a constraint for organization score, similarly for others.
2. $2x_2 = 2$ or $x_2 = 1$
3. $6x_3 = 6$ or $x_3 = 1$
4. $8x_4 = 8$ or $x_4 = 1$
5. $2x_2 + 6x_3 \geq 11$
6. $2x_2 + 8x_4 \geq 10$
7. $2x_1 + 6x_3 \geq 10$
8. $2x_1 + 6x_3 + 8x_4 \geq 8$
9. $2x_1 + 2x_2 + 8x_4 \geq 8$
10. $2x_1 + 6x_3 + 8x_4 \geq 9$
11. $2x_1 + 2x_2 + 8x_4 \geq 9$
12. $2x_1 - 9x_3 - 9x_4 \geq 0$
13. $6x_3 + 8x_4 \leq 19$
14. $2x_1 + 8x_4 \leq 12$
15. $2x_1 + 6x_3 + 8x_4 \leq 12$
16. $2x_2 + 6x_3 + 8x_4 \leq 20$
17. $2x_1 + 2x_2 + 8x_4 \leq 36$
18. $2x_1 + 2x_2 + 6x_3 + 8x_4 \leq 36$

## 4: Create the Gurobi model
We will now create a Gurobi model in Python.

```python
import gurobi

# Create a new model
m = gurobi.Model()

# Define the variables
x1 = m.addVar(name="x1", lb=0, ub=None) # hours worked by Hank
x2 = m.addVar(name="x2", lb=0, ub=None) # hours worked by Laura
x3 = m.addVar(name="x3", lb=0, ub=None) # hours worked by Bobby
x4 = m.addVar(name="x4", lb=0, ub=None) # hours worked by George

# Objective function
m.setObjective(1.49*x1 + 2.46*x2 + 7.06*x3 + 6.37*x4, gurobi.GRB.MAXIMIZE)

# Constraints
m.addConstr(x1 == 1, name="Hank_organization_score")
m.addConstr(x2 == 1, name="Laura_organization_score")
m.addConstr(x3 == 1, name="Bobby_organization_score")
m.addConstr(x4 == 1, name="George_organization_score")

m.addConstr(2*x2 + 6*x3 >= 11, name="Laura_Bobby_organization_score")
m.addConstr(2*x2 + 8*x4 >= 10, name="Laura_George_organization_score")
m.addConstr(2*x1 + 6*x3 >= 10, name="Hank_Bobby_organization_score")
m.addConstr(2*x1 + 6*x3 + 8*x4 >= 8, name="Hank_Bobby_George_organization_score")
m.addConstr(2*x1 + 2*x2 + 8*x4 >= 8, name="Hank_Laura_George_organization_score")
m.addConstr(2*x1 + 6*x3 + 8*x4 >= 9, name="Hank_Bobby_George_organization_score_2")
m.addConstr(2*x1 + 2*x2 + 8*x4 >= 9, name="Hank_Laura_George_organization_score_2")

m.addConstr(2*x1 - 9*x3 - 9*x4 >= 0, name="Hank_Bobby_George_organization_score_diff")

m.addConstr(6*x3 + 8*x4 <= 19, name="Bobby_George_organization_score_max")
m.addConstr(2*x1 + 8*x4 <= 12, name="Hank_George_organization_score_max")
m.addConstr(2*x1 + 6*x3 + 8*x4 <= 12, name="Hank_Bobby_George_organization_score_max")
m.addConstr(2*x2 + 6*x3 + 8*x4 <= 20, name="Laura_Bobby_George_organization_score_max")
m.addConstr(2*x1 + 2*x2 + 8*x4 <= 36, name="Hank_Laura_George_organization_score_max")
m.addConstr(2*x1 + 2*x2 + 6*x3 + 8*x4 <= 36, name="All_organization_score_max")

# Solve the model
m.optimize()

# Print the solution
if m.status == gurobi.GRB.OPTIMAL:
    print("Objective: ", m.objVal)
    print("Hours worked by Hank: ", x1.varValue)
    print("Hours worked by Laura: ", x2.varValue)
    print("Hours worked by Bobby: ", x3.varValue)
    print("Hours worked by George: ", x4.varValue)
else:
    print("The model is infeasible")
```

## 5: Symbolic representation
Here is the symbolic representation of the problem:

```json
{
    'sym_variables': [
        ('x1', 'hours worked by Hank'), 
        ('x2', 'hours worked by Laura'), 
        ('x3', 'hours worked by Bobby'), 
        ('x4', 'hours worked by George')
    ], 
    'objective_function': '1.49x1 + 2.46x2 + 7.06x3 + 6.37x4', 
    'constraints': [
        'x1 = 1',
        'x2 = 1',
        'x3 = 1',
        'x4 = 1',
        '2x2 + 6x3 >= 11',
        '2x2 + 8x4 >= 10',
        '2x1 + 6x3 >= 10',
        '2x1 + 6x3 + 8x4 >= 8',
        '2x1 + 2x2 + 8x4 >= 8',
        '2x1 + 6x3 + 8x4 >= 9',
        '2x1 + 2x2 + 8x4 >= 9',
        '2x1 - 9x3 - 9x4 >= 0',
        '6x3 + 8x4 <= 19',
        '2x1 + 8x4 <= 12',
        '2x1 + 6x3 + 8x4 <= 12',
        '2x2 + 6x3 + 8x4 <= 20',
        '2x1 + 2x2 + 8x4 <= 36',
        '2x1 + 2x2 + 6x3 + 8x4 <= 36'
    ]
}
```