On The StoryAlityTM Probability Calculus – and the Principle of Induction
So – with regard to developing scientific theories (say, of Screenwriting), a scientist must make observation statements, prior to making assertions or deriving Theories.
For example, an observation statement of StoryAlity Film/Story/Screenplay Theory on RoI (Return on Investment):
“Common story and film elements that are in the Top 20 RoI Films – and are not in the Bottom 20 RoI Films – may also be causal factors in the Top 20 Films’ success in becoming viral memes.”
However, once a theory exists, it is necessary to conduct experiments that will either prove – or conversely, falsify – the theory.
In “What Is This Thing Called Science?” (Chalmers 2000) Alan Chalmers summarizes and compares the work and views of science historians Kuhn, Popper, Lakatos, Feyerabend – and others – and asks:
‘Under precisely what circumstances is it legitimate to assert that a scientific law has been “derived” from some finite body of observational and experimental evidence?
A first attempt at an answer to this question involves the demand that, if an inductive inference from observable facts to laws is to be justified, then the following conditions must be satisfied:
1) The number of observations forming the basis of a generalization must be large.
2) The observations must be repeated under a wide variety of conditions.
3) No accepted observation statement should conflict with the derived law.
… The above can be summed up by the following statement of the principle of induction.
If a large number of A’s have been observed under a wide variety of conditions, and if all those A’s without exception possess the property B, then all A’s have the property B.’
To address these points with regard to StoryAlity Theory:
- 40 films of the empirical doctoral research study were examined, to form the generalisations of the StoryAlity theory. Since they are at the `extreme ends of the ROI spectrum’ (the 20 highest – and 20 lowest ROI films) the differences between them are extreme.
- The 40 films of the primary data set (the Top 20 ROI and bottom 20 ROI Films) span 70 years, from 1968 to 2010.
- The laws of holarchies and memes govern the behaviour of the top 20 ROI films within the feature film system and the paradigm of cultural evolution.
- Currently, to date (2012) no accepted observation statements conflict with the derived law/s.
It is also clear that, not all 20 of the top 20 films were not directed by name directors: 2 films, Star Wars and ET had famous directors attached. However – the other 18 of the 20 films were directed by unknowns.
Therefore the StoryAlityTM theory of “What empirically makes a theatrical feature film go viral?” means – there are not laws or even rules, but rather probabilities attached to the cause of a film going viral.
Also: a `black swan’ (in Sir Karl Popper’s terms) could indeed enter the Top 20 ROI Films list (i.e. a black swan in these terms would be a film that contains no `top 20 elements’ and all `bottom 20 ROI elements’, not the film “Black Swan” directed by Darren Aronofsky), and it would mean the probabilities would need to be recalculated in light of this new evidence. (See the section on Bayes’ Theorem elsewhere on this Blog, for more on this.)
ON FALSIFICATION, and the STORYALITY theory as a `boldly conjectured, novel, testable theory’
Chalmers also states:
`Little is learned from the falsification of a bold conjecture or the confirmation of a cautious conjecture.
If a bold conjecture is falsified, then all that is learnt is that another crazy idea has been proved wrong…
The falsificationist wishes to reject ad hoc hypotheses and to encourage the proposal of bold hypotheses as potential improvements on falsified theories.
Those bold hypotheses will lead to novel, testable predictions, which do not follow from the original, falsified theory.
However, although the fact that it does lead to the possibility of new tests makes an hypothesis, it will not rank as an improvement on the problematic theory it is designed to replace until it has survived at least some of those tests.
This is tantamount to saying that before it can be regarded as an adequate replacement for a falsified theory, a newly and boldly proposed theory must make some novel predictions that are confirmed. Many wild and rash speculations will not survive subsequent testing and consequently will not be rated as contributing to the growth of scientific knowledge. The occasional wild and rash speculation that does lead to a novel, unlikely prediction, which is nevertheless confirmed by observation or experiment, will thereby become established as a highlight in the history of the growth of science.
The confirmations of novel predictions resulting from bold conjectures are very important in the falsificationist account of the growth of science.’
It is worth noting that the film The Devil Inside (2012) was not one of the films in the set of 20 films that led to the StoryAlity theory; it only entered the top 20 ROI films data set after the initial study of the characterstics of the Top 20 ROI Films was completed – and the StoryAlity Theory had been formulated.
Fortunately – as the #14 ROI film, the film The Devil Inside (2012) adheres to the theories (`Villain Triumphant’; a writer-hyphenate; no character arcs, etc), it can be considered as one (in fact, the first) official and empirical proof of the StoryAlity theory.
Part of the StoryAlity hypothesis is that these Top 20 ROI films only appear every 2.05 years on average; given that The Devil Inside `arrived on time’ it would appear that the StoryAlity theory predicts that the next top 20 ROI film should not enter the top 20 ROI list until 2014.
On `complex webs of assumptions’ in scientific theorem:
There are a complex web of assumptions surrounding existing screenwriting theory, also known as: “the screenwriting convention”.
One of these (incorrect) assumptions is that: Screenplays written in accordance with the story theories in any (or all) of the major screenplay guru screenwriting manuals will succeed in going viral.
However `success’ – in terms of audience reached – is rarely (or never) addressed in these eight major screenwriting “How-To” texts, as the screenplay examples (and theories) provided for study are selective and illustrative – not comprehensive and evidentiary.
The StoryAlity™ theory aims to remove many of those incorrect assumptions.
It is for this reason the Top – and Bottom – 20 ROI films were selected, as the data set of the empirical study.
These other (problematic) `conventional’ screenwriting theories do not bear comparison with the historical evidence; they can be observed to represent a serious mismatch between nature (actual film performance within the feature film system) and screenwriting theory.
Notably, the StoryAlity™ theory is not historically relative nor historically contextual, it applies across time (i.e. specifically, across the past 70 years).
The common story elements in these films appear across the entire 70 year span of the data.
On the `Hard Cores’ and `Protective Belts’ of Scientific Theories:
When summarizing the conceptual framework of philosopher of science Imre Lakatos (with regards to the formal characteristics of science), Chalmers states:
‘Lakatos referred to the fundamental principles as the hard core of a research program.
The hard core is, more than anything else, the defining characteristic of a program. It takes the form of some very general hypotheses that form the basis from which the program is to develop.
Here are some examples. The hard core of the Copernican program in astronomy was the assumption that the earth and the planets orbit a stationary sun and that the earth spins on its axis once a day. The hard core of Newtonian physics is comprised of Newton’s three laws of motion plus his law of gravitational attraction. The hard core of Marx’s historical materialism would be something like the assumption that major social change is to be explained in terms of class struggle, the nature of the classes and the detail of the struggle to be determined, in the last instance, by the economic base.
The fundamentals of a program need to be augmented by a range of supplementary assumptions in order to flesh it out to the point where definite predictions can be made. It will consist not only of explicit assumptions and laws supplementing the hard core, but also assumptions underlying the initial conditions used to specify particular situations and theories presupposed in the statement of observations and experimental results…
Any inadequacy in the match between an articulated program and observation is to be attributed to the supplementary assumptions rather than the hard core.
Lakatos referred to the sum of the additional hypotheses supplementing the hard core as the protective belt, to emphasize its role in protecting the hard core from falsification.
According to Lakatos (1970, p.133) the hard core is rendered unfalsifiable by “the methodological decisions of its protagonists”.
By contrast, assumptions in the protective belt are to be modified in an attempt to improve the match between the predictions of the program and the results of observation and experiment.’ (Chalmers 2000: 131-2)
In other words, any research program (or, paradigm, in Kuhn’s terms) requires:
2) Assumptions and Laws
3) Assumptions about Initial Conditions
5) Observation and Experiment.
And the research program (or paradigm) should have a `hard core’ – and a `protective belt’.
With these stipulations by Lakatos in mind (and adhering to Kuhn, Popper and Feyerabend’s respective positions on the philosophy of science, and the principle of induction) – the `hard core’, in the case of StoryAlity Theory – would be:
1) The key hypothesis is that: Films succeed or fail, depending primarily on their Story alone;
2) The core assumptions of the hypothesis include that: The elements in those film stories can be empirically examined; and that writers/filmmakers can control (and, shape) the story of the films they make.
Laws would include that: Films with these viral story elements in them will succeed in spreading in the culture – and this will be reflected in their box office (as audience numbers directly correlate with box office)
3) Assumptions about initial conditions are that the conditions are similar for all films; that marketing, stars, director names, (etc) do not affect a film’s success in becoming a high ROI film. The exception is that a minimum of $1m in Marketing spend is required to enable any feature film sufficient insertion of its memes into the system. (If say only half of this spend is made, e.g. $500k instead of $1m, then the likelihood of the film story going viral is in fact reduced by 50%.)
4) Predictions of the StoryAlity Theory include that: Films that include more of the elements of these viral films have a higher probability of going viral (and therefore – higher probability of becoming high ROI films, or even becoming Top 20 ROI Films, if they adhere 100% to the Top 20 ROI Film Checklist and Guidelines) Given that The Devil Inside emerged, as predicted by the theory, 2 years after the previous film (Paranormal Activity, 2009) if a new top 20 ROI film emerged prior to 2014 (2 years later) then Bayes’ Theorem would then apply.
5) Observation includes: Noting when new films enter the Top 20 ROI list (for e.g. such as: The Devil Inside, 2012) and comparing their Film Story Elements/Memes with The StoryAlity Probability Calculus (i.e. all 30 elements of top 20 ROI films, and also observing that the films do not contain many or any elements of the bottom 20 ROI films.)
6) Experiment/s – include the creation of films according to The StoryAlity Film/Story/Screenplay Guidelines, and then empirically measuring and observing their ROI success (i.e. their `Audience Reach / Production Budget’)
The protective belt of StoryAlity theory: (the following are possible candidates/examples)
1) The Measurement Techniques: How do we know that the box-office figures and production budget details (for existing and `new entry’ films) are indeed accurate? Exactly how accurate are they? Could this result in false data for a new film, and thus, (erroneously) falsify the theory, due to measurement inaccuracy/bad data? The-Numbers.com data is the best ROI data currently available (as at 2012), yet it clearly involves box office and budgeting (and even Marketing Spend) reporting inaccuracies.
2) Anomalous conditions: How do we know what other (anomalous) conditions were present? (e.g. Horrifically, a lone gunman commits an atrocity in a cinema (e.g. as occurred during a US screening of the 2012 The Dark Knight Rises movie), and audiences in general stay away from cinemas, for some time.)
3) Historical Events: What if, something else occurred, that impeded the potential ROI success of a film? How would we know / What if we were not aware of these circumstances? (It would in fact require, among other things, monitoring the news, in all countries, at all times.)
With regard to the protective belt of a research program, Chalmers goes on to say:
`Early work in a research program is portrayed as taking place without heed or in spite of apparent falsifications by evidence.
A research program must be given a chance to realize its full potential. A suitable sophisticated and adequate protective belt must be constructed… When a program has been developed to the stage where it is appropriate to subject it to experimental tests, it is confirmations rather than falsifications that are of paramount significance, according to Lakatos.
The worth of a research program is indicated by the extent to which it leads to novel predictions that are confirmed. (Chalmers 2000: 135 – emphasis mine)
Figure 2 – Time Series of The Bottom 20 ROI Films
Data Source: Nash Information Services, LLC (2012), ‘Movie Budget Records’
Analysis: the author, JT Velikovsky – using data sourced from (Nash Information Services 1997-2012)
The time series of the 20 Biggest ROI Loser Films (above) shows that all 20 of them are contained between 1999 and 2010. In contrast – the Top 20 ROI films are from 1968 to 2009.
This means comparing 41 years of top 20 ROI, compared to 11 years of bottom 20 ROI – or in other words, the observation statement that: Films enter the bottom 20 list 4 times as frequently as the top 20. (This frequency also correlates with the finding that: 7 in 10 films lose money.)
With regard to the predictions of the key StoryAlity hypothesis, it is also important to distinguish between the novel prediction of phenomena – and – the prediction of novel phenomena.
Chalmers (2000) states:
`One of the most impressive features of quantum mechanics was its ability to explain the spectra exhibited by the light emitted from gases, a phenomena familiar to experimenters for over half a century before the quantum mechanical explanation was available.
These successes can be described as involving the novel prediction of phenomena rather than the prediction of novel phenomena.’
Chalmers also states that Science is: a web of `aims, methods, standards, theories, and observational facts’. (Chalmers 2000: 170)
The StoryAlity theory is therefore scientific and empirical in its methodology, and contains all of the above elements as outlined by Lakatos, and also: Experiment. (Whenever a film is released that intentionally adheres to The StoryAlity theory – please see StoryAlity posts #50 – #60 inclusive, for a summary of key elements of the theory.)
So – with regards the StoryAlity Theory, the above would constitute: a hard core, and a protective belt.
In terms of evolutionary epistemology, it should be noted that knowledge evolves… see this book chapter:
…Thoughts, Feedback, Comments always welcome.
High-RoI Story/Screenplay/Movie and Transmedia Researcher
The above is (mostly) an adapted excerpt, from my doctoral thesis: “Communication, Creativity and Consilience in Cinema”. It is presented here for the benefit of fellow screenwriting, filmmaking and creativity researchers. For more, see https://aftrs.academia.edu/JTVelikovsky
JT Velikovsky is also a produced feature film screenwriter and million-selling transmedia writer-director-producer. He has been a professional story analyst for major film studios, film funding organizations, and for the national writer’s guild. For more see: http://on-writering.blogspot.com/
Chalmers, A. F. (2000), What Is This Thing Called Science? (3rd ed. edn.; Buckingham: Open University Press).
Nash Information Services, LLC (2012), ‘Movie Budget Records – Most Profitable Movies, Based on Return on Investment’, Movie Budget Records <http://www.the-numbers.com/movies/records/budgets.php>, accessed 25th May.
The planet Saturn, as viewed from NASA’s Cassini spacecraft, 2012. Source: http://www.ciclops.org/view/7418/A_Splendor_Seldom_Seen)