
## 2.2 Analysis Of A Pivotal Scene, Scene 43

As a basis for a deeper look at Casablanca we have taken comprehensive but qualitative discussion by McKee [4] and sought quantitative and algorithmic implementation.

Casablanca is based on a range of miniplots. For McKee its composition is
"virtually perfect".

Following McKee [4] we will carry out an analysis of Casablanca's "MidAct Climax", Scene 43, subdivided into 11 "beats". McKee divides this scene, relating to Ilsa and Rick seeking black market exit visas, into 11 "beats".

1. Beat 1 is Rick finding Ilsa in the market.

2. Beats 2, 3, 4 are rejections of him by Ilsa.

3. Beats 5, 6 express rapprochement by both. 4. Beat 7 is guilt-tripping by each in turn.

5. Beat 8 is a jump in content: Ilsa says she will leave Casablanca soon.

6. In beat 9, Rick calls her a coward, and Ilsa calls him a fool.

7. In beat 10, Rick propositions her.

8. In beat 11, the climax, all goes to rack and ruin: Ilsa says she was married to Laszlo all along. Rick is stunned.

Figure 8 shows the evolution from beat to beat rather well. 210 words are used in these 11 "beats" or subscenes. Beat 8 is a dramatic development.

Moving upwards on the ordinate (factor 2) indicates distance between Rick and Ilsa. Moving downwards indicates rapprochement.

In the full-dimensional space we can check some other of McKee's guidelines.

Lengths of beat get shorter leading up to climax: word counts of final five beats in scene 43 are: 50 - 44 - 38 - 30 - 46. A style analysis of scene 43 based on McKee can be Monte Carlo tested against 999 uniformly randomized sets of the beats. In the great majority of cases (against 83% and more of the randomized alternatives) we find the style in scene 43 to be characterized by: small variability of movement from one beat to the next; greater tempo of beats; and high mean rhythm.

The planar representation in Figure 8 accounts for approximately 12.6% +
12.2% = 24.8% of the inertia, and hence the total information. We will look at the evolution of this scene, scene 43, using hierarchical clustering of the fulldimensional data - but based on the relative orientations, or correlations with factors. This is because of what we have found in Figure 8, viz. *change* of direction is most important.

Figure 9 shows the hierarchical clustering, based on the sequence of beats.

Input data are of full dimensionality so there is no approximation involved. Note the caesura in moving from beat 7 to 8, and back to 9. There is less of a caesura in moving from 4 to 5 but it is still quite pronounced.

Further discussion of these results can be found in [8].