## Step 1: Define the symbolic representation of the problem
The problem involves two variables: 'hours worked by Bobby' and 'hours worked by Bill'. Let's denote 'hours worked by Bobby' as $x_1$ and 'hours worked by Bill' as $x_2$. The objective function to maximize is $8x_1 + 5x_2$.

## Step 2: List the constraints in symbolic notation
The constraints given are:
1. Bobby's work quality rating is 7: $7x_1$ (but this seems to be a fixed attribute, not a constraint in the traditional sense. However, we have specific ratings and scores that need to be considered in the context of $x_0$ and $x_1$ for resources $r0$ and $r1$).
2. Bobby's organization score is 21: $21x_1$ (similarly, this seems to be a given attribute).
3. Bill has a work quality rating of 27: $27x_2$.
4. Bill has an organization score of 26: $26x_2$.
5. The total combined work quality rating must be greater than or equal to 49: $7x_1 + 27x_2 \geq 49$.
6. The total combined organization score must be no less than 50: $21x_1 + 26x_2 \geq 50$.
7. $-4x_1 + 3x_2 \geq 0$.
8. The total combined work quality rating must be less than or equal to 93: $7x_1 + 27x_2 \leq 93$.
9. The total combined organization score must be as much or less than 115: $21x_1 + 26x_2 \leq 115$.
10. $x_1$ can be a non-whole number of hours.
11. $x_2$ must not be a non-integer amount of hours.

## 3: Correctly interpret the resource attributes
Given resources/attributes:
- $r0$: {'description': 'work quality rating', 'upper_bound': 133, 'x0': 7, 'x1': 27}
- $r1$: {'description': 'organization score', 'upper_bound': 190, 'x0': 21, 'x1': 26}

These seem to imply that the work quality rating and organization score per hour for Bobby ($x_1$) and Bill ($x_2$) are given, but we actually need to directly use $x_1$ and $x_2$ as hours worked.

## 4: Formulate the symbolic representation
The symbolic variables are:
- $x_1$ for 'hours worked by Bobby'
- $x_2$ for 'hours worked by Bill'

The objective function is: $8x_1 + 5x_2$

The constraints are:
1. $7x_1 + 27x_2 \geq 49$
2. $21x_1 + 26x_2 \geq 50$
3. $-4x_1 + 3x_2 \geq 0$
4. $7x_1 + 27x_2 \leq 93$
5. $21x_1 + 26x_2 \leq 115$
6. $x_2$ is an integer.

## 5: Convert to Gurobi code
```python
import gurobi

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

# Define the variables
x1 = m.addVar(name="hours_worked_by_Bobby", lb=0)  # Assuming hours cannot be negative
x2 = m.addVar(name="hours_worked_by_Bill", lb=0, integrality=gurobi.GRB.INTEGER)

# Define the objective function
m.setObjective(8 * x1 + 5 * x2, gurobi.GRB.MAXIMIZE)

# Add constraints
m.addConstr(7 * x1 + 27 * x2 >= 49)
m.addConstr(21 * x1 + 26 * x2 >= 50)
m.addConstr(-4 * x1 + 3 * x2 >= 0)
m.addConstr(7 * x1 + 27 * x2 <= 93)
m.addConstr(21 * x1 + 26 * x2 <= 115)

# Optimize the model
m.optimize()

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

## 6: Symbolic representation in JSON format
```json
{
    "sym_variables": [
        ["x1", "hours worked by Bobby"],
        ["x2", "hours worked by Bill"]
    ],
    "objective_function": "8*x1 + 5*x2",
    "constraints": [
        "7*x1 + 27*x2 >= 49",
        "21*x1 + 26*x2 >= 50",
        "-4*x1 + 3*x2 >= 0",
        "7*x1 + 27*x2 <= 93",
        "21*x1 + 26*x2 <= 115",
        "x2 is an integer"
    ]
}
```