## Step 1: Define the symbolic representation of the variables
The variables are 'hours worked by Laura' and 'hours worked by Bobby', which can be represented symbolically as $x_1$ and $x_2$ respectively.

## Step 2: Define the objective function in symbolic notation
The objective function to maximize is $9x_1 + 4x_2$.

## Step 3: Define the constraints in symbolic notation
The constraints given are:
1. $0.46x_1 + 6.11x_2 \geq 37$
2. $-x_1 + 4x_2 \geq 0$
3. $0.46x_1 + 6.11x_2 \leq 102$
4. (Implicitly the same as constraint 3) $0.46x_1 + 6.11x_2 \leq 102$
5. $x_1$ and $x_2$ can be fractional.

## 4: Identify the resource/attributes and their bounds
Given resource/attributes:
- $r_0$: computer competence rating with $x_0 = 0.46$ for Laura and $x_1 = 6.11$ for Bobby, and an upper bound of 105.

## 5: Formulate the symbolic representation of the problem
The symbolic representation is:
- Variables: $x_1$ ('hours worked by Laura'), $x_2$ ('hours worked by Bobby')
- Objective function: Maximize $9x_1 + 4x_2$
- Constraints:
  1. $0.46x_1 + 6.11x_2 \geq 37$
  2. $-x_1 + 4x_2 \geq 0$
  3. $0.46x_1 + 6.11x_2 \leq 102$

## 6: Convert the problem into Gurobi code
```python
import gurobi

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

# Define the variables
x1 = model.addVar(name='hours_worked_by_Laura', lb=0)  # Laura
x2 = model.addVar(name='hours_worked_by_Bobby', lb=0)  # Bobby

# Define the objective function
model.setObjective(9 * x1 + 4 * x2, gurobi.GRB.MAXIMIZE)

# Define the constraints
model.addConstr(0.46 * x1 + 6.11 * x2 >= 37, name='min_computer_competence')
model.addConstr(-x1 + 4 * x2 >= 0, name='bobby_laura_ratio')
model.addConstr(0.46 * x1 + 6.11 * x2 <= 102, name='max_computer_competence')

# Optimize the model
model.optimize()

# Print the solution
if model.status == gurobi.GRB.OPTIMAL:
    print('Optimal solution found.')
    print(f'Hours worked by Laura: {x1.varValue}')
    print(f'Hours worked by Bobby: {x2.varValue}')
    print(f'Objective function value: {model.objVal}')
else:
    print('No optimal solution found.')
```

## 7: Provide the symbolic representation in JSON format
```json
{
    "sym_variables": [
        ["x1", "hours worked by Laura"],
        ["x2", "hours worked by Bobby"]
    ],
    "objective_function": "9*x1 + 4*x2",
    "constraints": [
        "0.46*x1 + 6.11*x2 >= 37",
        "-x1 + 4*x2 >= 0",
        "0.46*x1 + 6.11*x2 <= 102"
    ]
}
```