When (if ever) Is a Claim Objective?
“Objective”, as in, for example, “what I’m saying is objective”, or “that statement is objective”, or “we need objective criteria when making these decisions”, is a complicated term. It takes a lot of effort to make sure it is understood as intended (or closely enough). It is therefore a costly word to use. Why is that?
I was surprised to hear “objective” used a couple of times in “Worth“, a movie about Kenneth Feinberg’s role as Special Master of the U.S. government’s September 11th Victim Compensation Fund. In a scene early in the movie, the Feinberg character, played by Michael Keaton, says the following (between minutes 17 and 18 of the movie):
“There’s a process here, you know. I hire a team, I draft an objective formula, and I dispense reasonable payments.”
Later, the script has the Feinberg character saying this:
“We need to be objective toward them. That’s all.”
Above, “them” are the victims or relatives of victims of September 11 attacks. At another moment in the movie, a member of the team that works with Feinberg’s character in the movie says the following:
“If I can’t be objective, then maybe I shouldn’t be here.”
Leaving the movie aside, the “Final Report of The Special Master for the September 11th Victim Compensation Fund of 2001” [1] says the following (page 7 of that Report):
“The Regulations set forth guidelines for the determination of economic and non-economic loss and directed the Special Master to develop a methodology for computing ‘presumed’ economic and non-economic loss for claims on behalf of deceased victims based on objectively verifiable factors. The Special Master published detailed guidelines explaining the computation methodology and assumptions that would be incorporated into the calculations as well as charts showing computation examples. In order to minimize, as much as possible, the speculative nature of computing future economic loss, the presumed methodology relies on a combination of the victim’s own objectively verifiable historical experience with assumptions about likely future events based on publicly available national data.
In this manner, the methodology incorporates the individual circumstances of the victim and generally accepted non-speculative assumptions about the future. By recognizing the financial history of the victim through incorporation of individual income data and utilizing favorable assumptions about continuous wage growth and work life, the presumed award loss computations for most deceased victims provide the necessary financial support to the families in an individual tailored manner.”
“Objectively verifiable factors” above is the only mention related to something being “objective”; this isn’t a problem at all – my point is only to illustrate how much this is qualified through the paragraph above. It is the factors used in computation that are objectively verifiable, which probably means that these factors can be verified by different people, and that verification will yield the same conclusions. So this isn’t the “light” objectivity, so to speak, that’s in the movie script. When the movie character says that he will “be objective”, that’s something quite different than the commitment to provide objectively verifiable factors in the methodology for estimating presumed economic loss. Notice the commitment above to “minimize […] the speculative nature of computing future economic loss”.
Let’s return to the question we started with: Why is it costly to use the term “objective”? The example above seems to support that it is, and this should be apparent if you consider the following question: Does the paragraph above, from the Report, suggest that the methodology is objective, or that something else is objective, that is part of the methodology? If you are interested in that question, it is useful to read the “Explanation of Process for Computing Presumed Economic Loss” [2], and ask if the procedure outlined there is objective?
The reason I use the complex example as the one above, is that I don’t believe that there is a need to appeal to any part or whole methodology to “be objective”, for it to be useful and acceptable. Usefulness can be established through application. Acceptability is a matter of reaching agreement about the properties a methodology needs to satisfy, in order for those who accept it to, well, accept it.
Appeal to objectivity, in other words, can be both too ambitious and unnecessary. And indeed, there was no reason to state that objectivity was a goal of the Report, as visible from the excerpt below (page 12 of the Report):
“In sum, the Regulations, methodologies and policies adopted by the Fund were designed to accomplish several objectives: (1) provide full and complete information to the claimants, allowing informed choices about participation in the Fund, (2) ensure consistent and understandable awards through the adoption of clear-cut guidelines, (3) ensure generous awards consistent with the Regulations by resolving ambiguity and uncertainty in favor of the claimant, (4) allow claimants the opportunity to participate in an in-person hearing, (5) ensure that claimants who did not secure a lawyer or other expert would not be penalized in their opportunity to participate in the process and obtain a fair and consistent award, and (6) make certain that the staff of the Fund was accessible to claimants to answer questions and respond to concerns.”
This doesn’t discredit the movie script; I heard it said that characters in movies are vehicles for ideas, and the character that Keaton plays looks like a vehicle for the idea that it is possible to be objective when assessing the economic value of human loss. It is possible to be transparent, consistent, clear, systematic, and open to criticism – all valuable – but these together are still not enough for objectivity, as we will see below. So claiming to be objective, or that something you put forth is objective, might neither be useful, nor accurate.
What, then, is needed to claim objectivity? Is that possible at all?
In their overview of the concept of scientific objectivity, Reiss and Sprenger [3] summarized several views:
- Objectivity as faithfulness to facts: “scientific claims are objective in so far as they faithfully describe facts about the world”; “‘Objective’ then becomes a success word: if a claim is objective, it correctly describes some aspect of the world.” If this is possible, it is certainly great, as it helps resolve disputes in favor of the one that is objective. Objective claims would let us produce accurate predictions.
- Value-free ideal: Being objective may be to somehow remove or ignore values when doing the work that is needed to produce claims, and if so, those claims would be objective. The problem with this is that one will choose assumptions, make predictions, and build theories because that person is interested in the predictions, and therefore, in building theories, and so on. People do not randomly choose problems to work on.
- Objectivity as freedom from personal biases: “[a]ccording to this view, science is objective to the extent that personal biases are absent from scientific reasoning, or that they can be eliminated in a social process. […] objective scientific results do not […] depend on researchers’ personal preferences or experiences – they are the result of a process where individual biases are gradually filtered out and replaced by agreed upon evidence.”
To be objective, then, is to provide value-free, bias-free, and accurate claims about the world. If that does not work, however, and it frequently doesn’t, if we, instead, have imperfect claims, done from observations and manipulations of small samples, then objectivity can be the conclusion of an assessment across independently-produced scientific results: this is what reproducibility studies try to establish, and meta-analyses critically assess.
Objectivity, especially if explained by accuracy of claims about the world, is closely related to measurement: we want to make instruments, which when used according to the same protocol by different people, will yield the same results, independently from what these individuals may prefer, and independently from their biases. There are problems there as well.
“According to Hasok Chang’s account of early thermometry (Chang 2004), the problem was eventually solved by using a “principle of minimalist overdetermination”, the goal of which was to find a reliable thermometer while making as few substantial assumptions […] as possible. It was argued that if a thermometer was to be reliable, different tokens of the same thermometer type should agree with each other, and the results of air thermometers agreed the most. ‘Minimal’ doesn’t mean zero, however, and indeed this procedure makes an important presupposition (in this case a metaphysical assumption about the one-valuedness of a physical quantity). Moreover, the procedure yielded at best a reliable instrument, not necessarily one that was best at tracking the uniquely real temperature (if there is such a thing).
What Chang argues about early thermometry is true of measurements more generally: they are always made against a backdrop of metaphysical presuppositions, theoretical expectations and other kinds of belief. Whether or not any given procedure is regarded as adequate depends to a large extent on the purposes pursued by the individual scientist or group of scientists making the measurements. Especially in the social sciences, this often means that measurement procedures are laden with normative assumptions, i.e., values.”
A simpler way to be pragmatic with the term “objective” is to avoid it altogether and focus instead on asking and verifying possibly more specific values, and maintaining the definitions of these through open critique in a given community to which these definitions matter: for example, transparency, provision of explanations for claims, openness to criticism, testing for presence of personal bias, and so on. You can see that approach as substituting “objective” for many more values, and focusing on values whose applicability to a claim can be practically verified and evidence of verification are transparent and accessible to as many as possible.
- Feinberg, K.R., 2004. Final Report of the Special Master for the September 11th Victim Compensation Fund of 2001. Department of Justice, at https://www.hsdl.org/?abstract&did=450410
- Department of Justice, 2002, “Explanation of Process for Computing Presumed Economic Loss”, at https://www.justice.gov/archive/victimcompensation/vc_matrices.pdf
- Reiss, Julian and Jan Sprenger, “Scientific Objectivity”, The Stanford Encyclopedia of Philosophy (Winter 2020 Edition), Edward N. Zalta (ed.), at https://plato.stanford.edu/archives/win2020/entries/scientific-objectivity/
