Description & Inference; Types of Evidence
The problem of “facts” again – what constitutes facts? Factual judgments? Reasoned speculations? Opinions?
How is “description” used in your text different from a “descriptive claim”?
Description is used in your text on pp. 12 – 13 in a different way than we use it the phrase, “descriptive assumptions”, as an alternative to “reality assumptions”.
A “reality assumption” or “descriptive assumption” refers to the function it plays in addressing what a person believes is really the case, and does not need to be based on direct observation: Thus, “God exists” can be someone’s reality or descriptive assumption, because that person believes that God is an aspect of reality, even if that person never directly observes God. Even the reality or descriptive assumption that “people never change” may not be based only on direct observation, but may involve an “inference”, or a conclusion drawn, from a small sample of people someone observed.
Even some “observations” in science were initially indirect, or involved observing effects of “objects” or “entities” that were not directly observed. For instance, strictly speaking, we might observe the effects of gravity, than directly observe some entity called gravity. This also involves some philosophical questions as to whether “reality” consists of “entities” or “relations”.
We don’t presently observe all posited particles in “particle physics”. Initially, DNA was not directly observed, although now we can observe it.
“Description” in your text brings back the language of “facts”
“Description” in your text refers to “reporting what is seen or heard”, and that report is of “what is the case”, which is “usually verifiable by examination”. (pp. 12 – 13): “Descriptions, like a set of facts, are statements about what is or is not the case. A description is usually most helpful it it is as straightforward and impartial as possible. Generally, each item in a description is verifiable by examination.” (p. 12)
Notice that descriptions are simply “like a set of facts”, and “facts” are not yet defined. They are defined, in a somewhat controversial way, later in your text, on pp. 45 ff. However, the implication will be, when we compare descriptions to inferences (the next slide), that descriptions report the “bare” facts, without further interpretation, given that this is even possible.
“Descriptions and inferences often get intertwined, and our own values or points of view can influence the description.” [p. 12], is how the text admits that it is actually difficult to be impartial in “reporting what is seen or heard”. See later slides for examples.
Descriptions v. Inferences
A report of what is seen or heard, of “what is the case”, usually verifiable by examination, that is, state the observable characteristics, such as the height, weight, and hair and eye color of a person.
Often act as support for inferences.
Lacks a conclusion, which is why it is not an argument
Conclusions “drawn on the basis of a description or other sorts of evidence”; (p. 13);
“…not necessarily impartial, for they often involve an attempt to make sense of the evidence, not just report what is seen or heard.” (p. 13)
Involves an “interpretation” of the evidence.
There can be a “chain of inferences” (see next slide).
Inferences are used in daily life, as well as science, medicine and criminal investigations – they cannot be completely avoided.
However, we can be careful as to how we draw our inferences – some may seem more plausible than others; yet, even an implausible inference may be possible, and we may need a way to discount it.
An example of a chain of inferences
Everyone in the classroom hears someone screaming in the hallway. Each person might try to “report” what she or he heard, and this would constitute the description. However, does describing it as “screaming” and as “in the hallway” already involve an interpretation of what is happening, that is, can the “report” be completely impartial?
Then what inferences might be drawn from this “observation”? One person might infer that somebody outside the classroom is physically hurt and then infer that it is necessary to call security or an ambulance (that is, a chain of inferences); Another person might infer that there was only a verbal dispute between two people outside the classroom, and therefore, might not infer that it is necessary to call security; Yet another person might infer that there are people outside the classroom who are simply excited and talking very loudly, and might infer that is necessary to tell them to be quiet.
We could always leave the classroom and try to obtain a closer observation, but interpreting what we see might also involve diverse inferences.
The photograph on p. 16: figure 1.4
Look at the photograph on p. 16, figure 1.4, where the caption poses the questions: “What do you observe? What do you infer?” Try to describe what you see in the photograph without including any interpretation of what is happening? How easy is this to do?
What are some of your inferences as to what is happening in this photograph and how are they based on the description? Are some of your inferences also based on assumptions that are not strictly based on your observations of the photograph? Are there alternative inferences you could have made, and, if so, what are they?
In drawing inferences, we might need to entertain possible alternative inferences, before settling on one. In this way, inferences may also contain some uncertainty.
The need to entertain possible alternatives will also play a role in “circumstantial evidence”, as well as in trying to determine what causes a particular effect. (See later slides. We will also continue this discussion in our next unit on Deduction and Induction.)
So what is a “fact”, according to your text?
On pp. 45 ff, your text discusses the difference between “facts”, “factual judgments”, and various types of opinions, such as “reasoned speculations”, “public opinions”, “legal opinions”, and “conjectures”.
In a sense, your text replaces the division between facts and opinions with a continuum that is partly based on the author’s understanding of the difference between descriptions and inferences, and is partly based upon decreasing degrees of certainty from “facts” through “conjectures”.
However, “facts” need not be absolutely certain, and “conjectures”, although very uncertain, might not be impossible. Sometimes the author does treat “facts” as information upon which there is a agreement, while “conjectures” as simply diverse, based on individual taste or preference, but I will be partially revising her approach. In this latter sense, however, the continuum is one of decreasing agreement, but it does not specify how or when that agreement is ultimately reached.
“Facts”, according to your text fall into one of 3 categories: 1) empirically verifiable; 2) mathematical proofs; and 3) true by definition. (see next slide)
Facts as “empirically verifiable”
“Facts” as “empirically verifiable” can be taken in two senses:
Observable through the 5 senses and/or measurable; We see that Jason has blue eyes and blond hair; We measure this height as 6 feet tall. This seems to correspond to “description”.
“Empirically tested” observations of effects through experiments. Observation through the 5 senses is not alone sufficient here, as this also involves testing hypotheses, which are a type of opinion called “reasoned speculation”, and often involves inferences from samples, as when we make inductive generalizations, which are also never absolutely certain. We will investigate this further in our next unit on deduction and induction.
Philosophical assumptions that may underlie “empirically verifiable” facts
If facts rely on “empirical verification” in the first sense, do we hold certain reality assumptions as to what constitutes our “senses” and how many there are? Some scientists and some other cultures have proposed that there are more than 5 senses, such as the sensation of heat (or differences in temperature) or the sensation of internal bodily processes, etc.
If facts rely on “empirical verification” in the second sense, do we hold certain assumptions as what counts as “reality” before we start our experiments? In other words, are we confining “reality” to the physical world? Can we include the “cultural world”, and, if so, does how we define “culture” constitute a further “reality assumption”?, etc. Can we include the “psychological world”? Do these assumptions change over time? After all, there was once an experiment that tried to “weigh the soul”, by weighing the body before and after death, and interpreting the difference in body weights as indicating how much the soul that escaped the dead body “weighed”.
If “facts” are based on “experience”, as some people claim, are there reality assumptions as to what constitutes “experience”? Is it confined to “sense data”? Is it whatever we have “lived through” in our lives, which could then include “religious experiences” and “experiences” of art? Can it include an experience of “awe” or “wonder”, as in “wow, what an experience!”
“Facts” as mathematical proofs or “true” by definition
The axioms in mathematics, such as those in Euclidean geometry, are considered “true by definition”, as in the definition of “parallel lines” as never meeting, despite the fact that there exists a non-Euclidean geometry in which parallel lines do intersect. (Compare the latitudes of the globe to the longitudes that intersect at the North and South Poles.)
The mathematical proofs, such as those found in geometry, are considered “true by derivation” from the axioms, and often constitute what we call a deductive system of reasoning.
Other definitions can be treated as factual, but we have treated them as “reality assumptions”. For example, “bachelors” are by definition, in the English language, “unmarried men”. More strictly speaking, these were considered “analytic statements” by the philosopher, Immanuel Kant, and we are not concerned with them here.
Notice that “true by definition” is the only place that the author mentions “truth” in reference to facts. Does “empirically verifiable” necessarily imply that the facts are also “true” or simply that they have lots of evidence to support them?
Factual Judgments (or factual claims)
Factual Judgments (or factual claims) are not the same as facts – they are at least “one step removed from facts”, that is, they involve at least one inference drawn from earlier observations, and are not bare description. Here we see how the author relies, in part, on her distinction between description and inference, even though the latter can also be intertwined, as stated earlier.
The example the author gives is “Smog is bad for your lungs”, which involves inferences drawn from observations about the “ingredients in smog” and from “studies that show the effects of those ingredients on the respiratory system”. (p. 46)
Although the author does not point this out, interpretation of statistics also involves inferences, and so statistics (or “data sets”), strictly speaking, need not be considered “facts”. At best, they might be “factual judgments”, varying in certainty and reliability as depending upon how they are collected and how large and diverse the sample is from which the data was collected. (See also later slides.)
What is “opinion”?
“Opinions are often based on perception, individual taste, or emotion, relative to the point of view of the person(s) voicing the opinion.” (p. 46) Notice that the author says “often” here, and then goes onto to address “public opinion” as “a synthesis or shared view of the people”, “usually obtained by statistical studies or polls”. Thus, the former quote should not be taken as characterizing all opinions, and may be misleading in that respect. It characterizes only some opinions.
The text then considers 3 other types of opinions: 1) conjecture; 2) reasoned speculation; and 3) legal opinion. (See next slides).
After we discuss all 3 other types of opinion, we will see that it is not clear what holds these diverse types together under the rubric or umbrella term, “opinion”, except insofar as they might be less certain than “facts” and “factual judgments”.
The distinction between “facts” & “opinions” remains important in many arenas of life. For example, in law courts, “trial courts” are triers of the “facts of the case”, while the “appeals courts” only consider questions of “law” rather than questions of “facts”. However, as we shall see “legal opinions” handed down as rulings in legal courts, have the force of law, and can be as certain as “facts” are in other arenas, such as science. Moreover, what is admissible evidence in a trial court is not equivalent to what constitutes a “fact” in other arenas, such as medicine or science, although there may be some overlap as to what counts as fact.
“Reasoned Speculation” as “Informed Opinion”
“Reasoned Speculations” could be considered “informed opinions” in several different ways.
They may be opinions given by an “expert” in the field, which are informed by the expert’s expertise or knowledge. As such, we will consider them as “expert testimony” in the later slides on “types of evidence”.
They “could cite some evidence” in support of them. In this way, opinions can be based on “facts” or other types of evidence, whether or not they are proposed by an “expert”.
They include some hypotheses, especially in the realm of science, where they are tested through experiments; or in criminal investigations, where they can help further the investigation by suggesting where to locate more evidence that confirms or denies them.
“When people set out the reasons for an opinion, we now have an argument.” In other words, opinions can be important as conclusions to arguments.
“Legal Opinions” in U.S. Common Law
The rulings of law courts in the U.S., with which people are obligated to comply, are called “legal opinions”. That seems to make them seem as certain as either “facts” or “factual judgments”.
This is part of the “common law” tradition of the United States and England, which is also based on the role of precedent. The “legal opinions” of the courts set precedents for later cases that become before the courts. This is often found in “civil law” (the arena of lawsuits), such as liability law – for example, who is responsible if a bottle of soda explodes in a consumer’s hands?
The type of reasoning by precedent is a form of reasoning based on analogy, which is another type of evidence we will be discussing in later slides.
“Conjectures” are opinions that are unsupported; they are “pure speculation” instead of “reasoned speculation”.
I do not think that the text gives good examples of “conjectures”. The examples the text gives are really “value claims” (e.g., “The best music is rhythm and blues”), which, as we shall see, is yet another type of evidence.
Conjectures can actually be found in all fields, even science, although, in science, scientists try make their unfounded hypotheses into hypotheses that could eventually be tested by specifying how they may be potentially confirmed or rejected by future evidence or experimentation, even if it is not possible to do so right now.
Types of Evidence – pp. 93 – 105 in text; summarized on pp. 102 – 103
Why have so many types of evidence? Each type of evidence lends itself to a different sort of evaluation, and ultimately we are interested in evaluating the arguments we set up in standard form.
We will not emphasize facts, factual judgments, and types of opinions when identifying types of evidence, whenever it is possible to be more specific, by identifying statistics, cause and effect reasoning, testimony, analogies, value claims, conditional claims, etc.
However, sometimes it will be very useful to identify “reasoned speculations”. Remember also that what is sometimes presented as “fact” is not necessarily “true”. We would need to “fact check” all so-called “facts” for their accuracy.
We will not emphasize “credible sources”, whenever it is possible to identify “expert testimony” or some other type of evidence instead. For example, the text tends to include government agencies as “credible sources” (p. 96), but if we are looking at the statistics gathered by government agencies, then we should identify the type of evidence as “statistics”. Those statistics, even if gathered by a government agency, are only as reliable as to how, and from whom, they are collected, and how successfully they have been collected, even when the agency follows a solid research design for their statistical studies.
Remember that “facts” and “factual claims” are not the same thing. Disregard “speculation or opinion” in the summary on p. 103, because it is misleading. Rely on the previous slides for any discussion of facts, factual judgments and different types of opinions.
Types of Testimony: Recommended course reserves reading: “Your Brain on Trial”
Eyewitness Testimony: includes the descriptions and reports by those who directly observe some event; it is not necessarily reliable even when eyewitnesses are not deliberately lying, because
1) problems in trying to impartially describe any event (see earlier slides);
2) problems with how we remember what we observe: memory tends to “reconstruct” the past rather than “photograph” it, so it can also be influenced by present events and leading questions.
Types of Testimony: Expert Testimony
Expert Testimony: preferred to the term, “credible source”, whenever possible; The idea is that there are qualified authorities on various types of knowledge, whom we can trust to give us either the “facts” or “informed opinions” in their area of expertise.
An “appeal to an unqualified authority” is a fallacy (that is, an error in reasoning) and the testimonials of celebrities or famous people are often considered examples of this fallacy, and sometimes a “propaganda technique” as we will learn in the last unit of this course. What would this say about the use of celebrities in “Half the Sky”?
All appeal to expert testimony could be seen as fallacious, to the extent that they were are then encouraged to replace “reasons” with “authority”. After all, even experts can be wrong, and how should we go about evaluating what they tell us? Are we always in a position to evaluate what they tell us? See the last page of the course reserves article, “Materials and Exercises on Fallacies”: “An Expert Said That?”
Types of Testimony: Anecdotes & Confessions
Anecdotes: includes examples and stories about a person/event, often used to vouch for the character of a person. Statistics, in their most basic form, can be seen as a date set of many examples.
Anecdotes may provide a more comprehensive “understanding” of one person’s experience or of an event, but can also lend themselves to the fallacy of “hasty generalization” from a sample set that is simply too small to draw the conclusions that it does.
Anecdotes can provide material for making hypotheses that can then be further tested with larger samples.
Anecdotes can include “stories” by medical clinicians of individual patients whom they have seen in their practices.
“Confessions”: People can confess to things they have not done, so even confessions need not be reliable. See again “Your Brain on Trial” (not required).
Circumstantial evidence occurs when there is no direct evidence (such as eyewitness testimony), but rather relies on such indirect evidence as “fingerprints, DNA & other physical evidence, & business records.”
“Circumstantial evidence has been strong enough to convict people of murder, even in the absence of a body!” (p. 98)
All the indirect evidence taken together (that is, with corroborating evidence that reinforces it), points to one likely conclusion. In the absence of any reasonable alternative or conflicting evidence, this conclusion seems more likely (although not certain).
Therefore, it is important to entertain and discount alternative accounts.
Conditional Claims: “if, then” statements
The “if” clause is the antecedent, that is the condition upon which the “then” clause depends; The antecedent need not be true (“If I had a million dollars….”). The “then” clause, or “consequent”, states the result or implication that follows, given that the antecedent holds.
Conditional claims are often used to express hypotheses.
Some conditional claims seem to express cause and effect relationships: “If the glass vase is dropped on the marble floor, then it will break” seems to say that dropping the vase will cause it to break.
However, conditional claims do not necessarily express cause and effect relationships: “If the light goes on on the printer, the printer is in the process of printing the material.” In this case, the light does not cause the printing, but is the “sign” that the printing is occurring.
Scope of Claim: “what the claim is meant to cover”
Universal claims: “All” of an entire class of “things”: “All humans are mortal”. “No human is 10 feet tall.”
Particular claims: “At least one”, which means that particular covers a lot of territory, including one, some, many, a majority, that is, almost everything that is not “all” or “none”.
However, how do we decide on the content of a universal claim? In the above example, “All humans are mortal”, do we observe a subset of humans, and decide to generalize that this is always the case?
Universal claims can be “disproven” by one counterexample, that is, if we could find one human who lived forever, then “All humans are mortal” would be false.
However, some philosophers, such as Aristotle, treated some universals as “for the most part”, and not absolutely always with no exceptions.
Other Types of Evidence
“Value claims may be used as evidence but they should be handled carefully.” (p. 97): Basically the same as value assumptions, but the text gives examples of different types: judgments of taste, aesthetic judgments (of art); and moral judgments.
Statistical evidence: We will be discussing this in more detail in Unit #3. Statistics need not be facts and do not “speak for themselves”. (See p. 98)
Cause and Effect Reasoning: Alternative causes must be discounted or dismissed, before accepting a cause or causal factor. We will discuss cause and effects in more detail in Unit #3 of the course.
Analogies: See the earlier slide on “legal opinions” and “precedents”. Analogies involve comparisons to draw conclusions from what is known to what is unknown. They only work insofar as the comparison of what is known is actually relevant and the similarities outweigh the differences.