Past exam of the philosophy of science supplementary subject of the University of Oxford / 2015 (A14139W1)

Source paper: www.whatdotheyknow.com/request/oxford_physics_past_papers_2/response/2340696/attach/3/Physics%20Papers%202014.pdf?cookie_passthrough=1. The dated cover identifies Hilary Term 2015, 17 March; the annual bundle filename says 2014. Both alternatives in question 2 are answered.

Hardness is no more automatically a primary quality than redness. The comparison turns on whether one means an experienced sensation, a disposition to affect a perceiver, or a physically specified property of a material. Keeping those three levels distinct supports a useful distinction without treating either tactile or visual experience as a direct copy of an object's constitution.

John Locke's list of primary qualities includes extension, figure, number, motion and solidity. A secondary quality is instead a body's power, grounded in its constitution, to produce a sensory experience. The colour experience does not literally resemble the shape or motion of the particles producing it. Crucially, Lockean solidity is not hardness. In the former account, both water and a diamond exclude another body from the space they occupy; they differ in how readily their parts move aside. In book II, chapter IV, section 4, John Locke explicitly treats ordinary judgments of hard and soft as relative to the human body's response. Thus his own distinction does not warrant simply assigning everything felt by touch to the primary class.^[ref]

A tactile example makes the distinction intelligible. The same surface may resist a fingertip yet yield to a harder indenter. Its measured hardness also depends on the load, test geometry and material state. Its resistance is nevertheless reproducible under specified conditions. Similarly, perceived color depends on the illuminating optical spectrum, the surface's reflectance and the perceiver's color vision. A change of illumination can change an appearance without changing the surface. In neither case does dependence on specified conditions make the material's response fictitious. A disposition can be an objective feature of how something behaves in a specified interaction.

One proposed boundary therefore separates properties specified independently of a particular kind of perceiver from properties defined through perceptual responses. This classifies redness understood as a visual disposition differently from a spectral reflectance function. It likewise separates felt resistance from a specified mechanical hardness test. The boundary does not coincide with vision versus touch, or with measurable versus unmeasurable. Both colour-related and mechanical responses admit quantitative investigation; both can be relational.

There are limits to a stronger metaphysical interpretation. George Berkeley argues that perceived size, shape and motion also vary with perceptual circumstances; experience does not simply present an invariant class of primary qualities while presenting only relative secondary qualities. That challenges an easy appeal to resemblance. It does not, without further argument, show that there is no perceiver-independent structure, since variability of appearances is compatible with stable relations explaining the variation.^[ref]

The defensible conclusion is consequently qualified. Experienced hardness has no privileged immunity from the difficulties raised by redness. A distinction between perceptual responses and the physical organization explaining them remains useful, but its physical side must be established by inquiry. It is not an unrevisable list certified by whichever sense first reveals a property.

Nelson Goodman's new riddle of induction asks which descriptions of an observed regularity are fit for projection. David Hume's problem of induction asks how a projection beyond experience can be justified at all. The problems are related, but accepting that experience supports some expectations does not settle which predicates an acceptable inference may project.

Fix a future time $t$ and let $E_t(x)$ mean that $x$ was examined before $t$. Define grue bySuppose every emerald examined so far is green. Each is then also grue. The same positive instances fit both a green generalization and a grue generalization, although the latter assigns blue to an emerald first examined after the cutoff. This does not require an already examined green emerald to change colour at $t$: its classification uses whether it was examined before $t$, not whether the present time is before $t$. The problem concerns incompatible projections to unexamined objects.^[ref]

It does not resolve the difficulty to object that grue is artificially disjunctive. Introduce the converse predicate, bleen, for examined-before-$t$ blue objects and other green objects. Green can then be defined using grue, bleen and $E_t$. Syntactic simplicity depends on which predicates are primitive. Nor does calling green a genuine natural kind settle matters unless one explains how the relevant natural structure is identified without simply presupposing the preferred projection. Evidence about stable material composition can provide a scientific reason to project a colour response, but that reason goes beyond counting instances.

David Hume's argument exposes a different gap. The denial of an unobserved continuation is not a contradiction. An appeal to the past success of extrapolation already extrapolates from past cases, so cannot supply a noncircular demonstration of its general reliability. His discussion of necessary connection similarly distinguishes experienced successions from an independently perceived necessity binding events together. These claims concern the basis of causal and predictive inference, not merely the spelling of a predicate.^[ref]

Predicate entrenchment is Nelson Goodman's proposed way of distinguishing established projective practices. Green has a history of actual use in projections which its newly constructed rival lacks. This gives a practice-based account of projectibility, rather than an unconditional guarantee that familiar classifications are true. Its weakness is that an account must still permit scientifically successful innovations and correction of entrenched mistakes.^[ref]

Thus Nelson Goodman sharpens the problem facing scientific confirmation: a purely formal positive-instance rule is too permissive. A defensible response combines explicit background assumptions with revisable standards for selecting predicates. That explains why two syntactically parallel generalizations need not receive equal support; it does not provide the noncircular guarantee demanded by the strongest reading of David Hume's challenge.

The raven paradox combines a plausible equivalence principle with an overly unrestricted account of positive-instance scientific confirmation. Let $R(x)$ and $B(x)$ mean that $x$ is a raven and black respectively. ThenA white shoe is a positive instance of the right-hand generalization. If every positive instance confirms its universal generalization, and logically equivalent statements receive the same evidential support, inspecting the shoe seems to confirm the original raven claim. There is no contradiction in the equivalence itself. The tension concerns the evidential rule and the intuition that an arbitrary shoe teaches us nothing about birds.^[ref]

The right response is to make background knowledge and sampling explicit. Under Bayesian confirmation, evidence increases support for $H$ precisely when its likelihood is greater under $H$ than under the alternative, assuming nondegenerate prior probabilities. A fact can therefore be compatible with $H$ yet provide no new support. The mere existence of a white shoe does not determine the needed likelihood ratio.^[ref]

Consider a deliberately simple finite model. There are $N$ objects, exactly $r$ ravens, and $M=N-r$ nonravens, with $M>r>1$. All nonravens are white. Under $H_0$ all ravens are black; under $H_1$ exactly one raven is white. Draw uniformly from the entire population. The event of drawing a white nonraven has probability $M/N$ under either hypothesis. Its Bayes factor is one and it leaves the prior odds unchanged. A black raven instead has likelihoods $r/N$ and $(r-1)/N$, so gives Bayes factor $r/(r-1)$ for $H_0$.

Now change the protocol: draw uniformly from the white objects, then discover that the selected object is a nonraven. This result has likelihoods $1$ and $M/(M+1)$. It gives the small positive Bayes factorFor $N=1000$ and $r=10$, this is $991/990$, whereas sampling a black raven from the full population gives $10/9$. The white nonraven can now help because the search could have revealed a white raven. The two experiments have different selection information, so their differing evidential values do not violate logical equivalence.

This model establishes possibilities, not a universal numerical law about shoes. Different alternatives, population information or selection procedures change the result. If the shoe's being a nonraven was already known, discovering that it is white need not add anything. Conversely, ruling out a potential counterexample can supply a small amount of information. Retain logical equivalence, but reject the unconditional instance-confirmation rule. Once the complete evidential situation is specified, neither zero support nor weak positive support is paradoxical, and neither amounts to proof of a universal law.

The transition from phlogiston theory to an oxygen theory of combustion, and the transition from Newtonian mechanics to special relativity, support a restricted account of incommensurability. They show changes in conceptual organization and standards of explanation. They do not establish that rival scientists cannot communicate, compare results or give reasons for preferring a new account.

In the chemical case, a common phlogistic treatment makes a metal a calx combined with phlogiston, so calcination removes the principle responsible for its metallic character. Antoine Lavoisier's treatment reverses the decomposition: a metal combines with part of the air to form the calx. In a closed vessel, the calx's gain in mass must be understood together with what happens to the remaining gas. The mercury-and-air investigation and the recovery of the gas from the calx organize these operations into a different account of composition. This is a change in the relations between elements, compounds and chemical processes, not merely a new name for an unchanged substance.^[ref]

For Thomas Kuhn, a translation which replaces every occurrence of phlogiston with one modern substance fails to preserve those interconnected roles. Yet historians can learn the earlier vocabulary and reconstruct the relevant experiments. His later account explicitly distinguishes interpretation and language-learning from a word-for-word translation into a fixed successor vocabulary. Local untranslatability does not imply that every term or observation is inaccessible to the other community.^[ref]

The mechanical example concerns the reorganization of space, time and motion. In special relativity, distant simultaneity depends on an inertial frame and a specified clock-synchronization procedure. Newtonian mechanics instead uses a common time independent of inertial motion. This affects more than numerical corrections to one law: it changes which events are simultaneous and how velocity and momentum are related.^[ref]

Nevertheless, quantitative comparison is possible. For an invariant rest mass $m$,Here $c$ is the speed of light and $\gamma$ the Lorentz factor. At $v=0.6c$, the respective momenta are $0.75mc$ and $0.6mc$, a directly comparable difference. For $v/c\ll 1$, the leading agreement explains an important domain of earlier success. It would be inaccurate to claim that modern special relativity invariably makes mass velocity-dependent: invariant rest mass remains invariant in this convention.

These examples therefore support conceptual discontinuity without total evidential isolation. Some explanatory aims and classifications change; many preparations, measurements and quantitative relations remain comparable. No unique algorithm follows from shared values such as accuracy and scope, but the absence of such an algorithm is weaker than the absence of rational assessment. The most defensible Kuhnian conclusion is local and historical: comparison can require learning a conceptual system, while still permitting criticism of both systems and empirically warranted preference between them.

For Karl Popper, scientific theories may be provisionally preferred and used because of their performance in tests. They are not thereby established as true, or assigned a high inductive probability of truth. The apparent ambiguity disappears when acceptance as a working conjecture is distinguished from acceptance as an evidentially justified universal conclusion.

A finite collection of successful predictions does not deductively entail an unrestricted universal theory. Karl Popper therefore rejects a method which first collects unquestionable observations and then derives a theory from them by inductive reasoning. His alternative is to formulate a conjecture, deduce discriminating consequences and try to refute it. A theory which survives demanding tests receives scientific corroboration, a retrospective appraisal of its test performance. In the primary account, this expressly differs from establishing the theory as true or even probable.^[ref]

There is consequently a legitimate evidential preference. Suppose one theory makes an independently checkable prediction which its main rival does not make, or contradicts. Successful testing gives a reason to retain and develop the first theory relative to that rival. Merely adjusting a conjecture to fit a known result need not provide as severe a test as a result for which it faced a genuine opportunity for failure. Temporal novelty alone is not the issue: an independently derived consequence can be demanding even when the relevant observation was already known. Repeating easy observations does not automatically provide the same scientific corroboration as exposing a theory to a new and discriminating risk. Acceptance remains conditional on the testing background and open to subsequent criticism.^[ref]

Acceptance also occurs at the level of basic statements. A test requires an agreed report about an observable event in specified circumstances. The participants can subject that report to further checks, but an investigation must provisionally stop somewhere if it is to yield an outcome. In sections 29–30, Karl Popper describes that stopping point as a rule-governed decision or agreement. Experience can prompt such a decision without logically proving the accepted report. This is neither an infallible observational foundation nor permission to choose the result arbitrarily.^[ref]

The Duhem problem adds a qualification. If $T\wedge A\Rightarrow E$, failure of $E$ contradicts the conjunction, not uniquely $T$. The auxiliary hypotheses $A$ include calibration and initial conditions. A reproducible failure may rationally lead to revising one of these instead. The critical question is whether the repair has independent testable consequences, or merely immunizes the favoured conjecture. Logical falsifiability alone does not decide that methodological issue.

A remaining objection is that choosing the best-tested theory for a future application seems to rely on past success. Karl Popper offers a critical preference among available conjectures, not a proof that the next application will succeed. Whether that answers the practical aspect of the problem of induction is disputable. It should not be resolved by silently redefining scientific corroboration as predictive certainty. Evidence matters to provisional selection and rejection; it never converts a scientific theory into an unrevisable established truth.

The analytic-synthetic distinction is proposed as a distinction between kinds of truth, not as an empirical discovery about a particular substance or force. An analytic truth is supposed to hold through meaning and logic; a synthetic truth depends additionally on how the world is. The absence of a laboratory discovery establishing that division neither automatically refutes it nor grants it immunity from criticism. Its status depends on whether a clear and useful distinction can be specified.

Consider an explicitly defined language. Let $B(x)$ mean bachelor, $U(x)$ unmarried, and admit the meaning postulateEvery interpretation admitted by that rule makes the sentence true. This is a precise relative notion of analyticity: the rule helps determine what the symbols mean. By contrast, a claim about how many people satisfy $B$ requires information about the population. The latter is not made true merely by adopting a vocabulary. Rudolf Carnap's meaning postulates explain how a chosen language can impose such semantic constraints without reducing every analytic sentence to a visible repetition of its subject.^[ref]

Two further distinctions must be kept separate. Analyticity concerns meaning and truth conditions; knowing something independently of a particular empirical investigation concerns justification. Necessity concerns whether it could have been otherwise. Treating these as interchangeable would assume rather than establish the most controversial part of the account. Even a conventional choice of language can generate nontrivial consequences whose derivation requires considerable reasoning.

Willard Van Orman Quine challenges a sharp, framework-independent boundary. An explanation of analyticity by synonymy may presuppose analyticity when explaining what counts as genuine synonymy. A dictionary records accepted usage; it does not independently establish why substitution preserves truth by meaning alone. The wider argument rejects the assumption that each empirical sentence confronts experience in isolation. Definitions, background assumptions and substantive claims work together in an evidential system. This is a philosophical criticism of proposed accounts, not an experimental finding that two previously measurable truth-types are physically identical.^[ref]

For philosophy of science, the important consequence is that neither logic nor observation should be credited with doing the other's work. In Euclidean geometry, a conclusion can follow from specified axioms; whether physical space satisfies the relevant geometry is a separate issue. Similarly, defining momentum as $mv$ in a model does not alone establish that this quantity is conserved in every physical interaction. A formal relation can be fixed by stipulation while the model's applicability remains empirical.

The best position is therefore neither that science has discovered an absolute cleavage nor that all useful distinctions disappear if an absolute cleavage fails. Analyticity relative to explicit rules is intelligible; an unrevisable division of all scientific language requires further argument. Scientific practice can retain definitions, deduction and a distinction between stipulation and measurement while allowing revision of frameworks and rejecting a simple separation of completely theory-free observations from an eternally fixed conceptual scheme.

There is defensible scientific progress, but it is not well characterized as an uninterrupted accumulation of truths or an inevitable march toward one complete description. Progress can consist in improved empirical discrimination, more accurate and wider-ranging predictions, better scientific explanation, and greater capacity to intervene reliably. Those achievements must be assessed against specified aims and competing accounts, rather than inferred from a theory's being later in time.

The physical content of an improvement matters. A model that fits a fixed data set using arbitrarily many adjustable parameters has not thereby supplied a stronger prediction. Independent tests, specified error bounds and successful application in new conditions distinguish a genuine extension of knowledge from a re-description of familiar results. An apparent failure can itself be progressive when it identifies the boundary of a model's applicability and supports a more reliable successor. More equations or more favourable observations are not enough by themselves.

The relation between Newtonian mechanics and special relativity illustrates a qualified retention of success. With invariant rest mass $m$, relativistic kinetic energy is $(\gamma -1)m{c}^2$. Its low-velocity expansion isThe first term recovers the familiar kinetic-energy expression in a controlled domain; the correction identifies a systematic departure. The successor can preserve successful low-speed calculations while revising the conceptual description of space and time. This demonstrates a relation between models, not that every statement in the earlier framework was true or that the successor is beyond further revision.

Thomas Kuhn's account gives normal science a comparatively clear measure of progress: increasingly effective solution of problems within an accepted scientific paradigm. During revolutionary theory change, the problems, classifications and standards themselves can partly change, and some older achievements may be lost or devalued. His chapter on progress nevertheless emphasizes growing problem-solving capacity; his position is not simply that no improvement occurs. The difficulty is explaining comparison across changes without treating the later community's preferences as automatically decisive.^[ref]

A scientific realist may interpret improved prediction as evidence of a more accurate account of the world. That is a further argument, not the definition of every successful calculation. Larry Laudan's historical objection warns that earlier successful accounts contained central commitments later rejected. Structural realism offers a selective response: ask which interpreted quantitative relations survive, and in which domains, rather than credit the entire old account with approximate truth.^[ref][ref]

The most reasonable conclusion is plural but not indiscriminate. Better error control, wider empirical reach and the identification of previously unknown phenomena provide substantive achievements, although they do not always increase together. Scientific progress is fallible, domain-sensitive improvement in our ability to investigate, predict and explain. A general guarantee of convergence to final truth is stronger than these achievements require, while denying every basis for comparison ignores the controlled relations and independent successes which inquiry can establish.

The deductive-nomological model represents an explanation as a valid deduction of an event description from scientific laws and particular circumstances. In the schemathe premises are the explanans and $E$ the explanandum. At least one law must be essential to the derivation, the premises must have empirical content, and a correct explanation must have true premises. Carl Hempel and Paul Oppenheim distinguish these adequacy requirements from merely giving a valid argument. Their developed 1948 analysis concerns deductive explanation; its name should not be extended without qualification to every statistical explanation.^[ref]

The model captures something valuable. For an ideal simple harmonic oscillator, the equation of motion $m\ddot{x}=-kx$, a positive mass $m$, a positive spring constant $k$ and non-equilibrium initial conditions determine a periodThe derivation explains why the period changes with those parameters within the model. It is not just the report that an oscillation occurred. Since a real spring may have damping or nonlinear response, applying the explanation requires justification of the approximation. The model's truth condition cannot turn an idealized calculation into a literally exact account of every laboratory spring.

The account is not sufficient to settle explanatory direction. For a vertical pole of height $h$ on level ground, a solar elevation angle $0<\theta <\pi /2$ and parallel light rays give a shadow length $\ell =h\cot \theta$. Given $h$ and $\theta$, one can deduce $\ell$; given $\ell$ and $\theta$, one can equally deduce $h$. Both calculations can use the same true optical and geometrical assumptions. Yet normally the pole and illumination explain the shadow, whereas measuring the shadow provides evidence about the pole's height. Deducibility does not distinguish this evidential inference from a causal explanation. This is the problem of explanatory asymmetry.

Nor is strict deduction necessary for every good physical explanation. A radioactive decay model can explain a sample's decay rate and the chance of a nucleus decaying in a specified interval, while not entailing which particular nucleus decays first. The exponential distribution supplies a controlled statistical account. Adding the observed result as a premise would permit a deduction but would not supply the missing explanation. An inductive-statistical model is a different proposal, and even that needs an account of which statistical information is relevant.

These objections do not show that every explanation must instead recount a sequence of causes. Explanations based on conservation laws or symmetry can constrain a phenomenon without specifying a detailed mechanism. The important point is that the role of the premises, the question being asked and the relevant dependence matter, in addition to logical consequence. The deductive-nomological model is a useful pattern for some physical explanations, but it is not an adequate necessary-and-sufficient account of explanation throughout the physical sciences.

Empirical equivalence must be specified relative to a domain and an account of what counts as observable. Two theories may fit all evidence collected so far while predicting different future results; that is ordinary underdetermination by a finite record. A stronger equivalence requires the same observable consequences for every permitted experiment in the stated domain. For stochastic predictions, matching a set of possible outcomes is not enough: the theories must assign the same outcome probability distributions under corresponding preparations and testing assumptions.

A clear physical example at the level of descriptions occurs in electromagnetism. Write the electric field and magnetic field using a scalar potential $\varphi$ and magnetic vector potential $\mathbf{A}$:For a smooth, single-valued function $\chi$, the gauge transformationleaves both fields unchanged: the curl of a gradient vanishes, and the mixed derivatives cancel in the electric-field expression. With the same charges, boundary conditions and force law, these descriptions give the same classical measurements. Agreement is structural, not an accidental fit to a few readings. However, many physicists regard such descriptions as representing one physical situation, so this alone is not an example of two genuinely incompatible physical theories. The smooth global transformation assumption also matters; equality of local fields is not an unrestricted license to identify every globally different potential configuration.

A second example exhibits possible surplus structure. For particles interacting by Newtonian forces depending only on relative positions, a common Galilean transformationleaves relative positions and accelerations unchanged. Accordingly, adding a privileged but completely uncoupled state of uniform rest does not alter any internal mechanical prediction. Rival choices of that unobservable rest state cannot be distinguished by these experiments. This is a deliberately specified completion of the mechanical model: it does not show that rotation or acceleration is undetectable, or that Newtonian mechanics and special relativity are empirically equivalent. The latter give different high-speed predictions. Whether undetectable absolute rest makes a genuinely different theory or a redundant representation is precisely one philosophical issue raised by the example.

Thus there are concrete cases of empirical redundancy, while the existence of equally well-motivated, fully distinct rivals with identical consequences across all physics is a much stronger claim. Historical theories often agree only in limited regimes or after additional assumptions. One must not convert that restricted agreement into an equivalence theorem for every possible test.

The philosophical relevance does not depend on finding a complete historical pair. A constructed rival can expose the logical limits of evidence, although an artificial extension need not deserve the same credibility as an economical account. If two specified models have equal likelihoods for every admissible data set $D$, thenfor finite positive prior odds. The Bayes factor is one; the data do not discriminate between them. Choices about simplicity or interpretation would be additional considerations. Constructive empiricism treats empirical adequacy as the relevant belief commitment in acceptance, while a scientific realist must explain what further warrants belief in the unobservable structure. The equivalence argument identifies a limit of evidential discrimination; it does not establish that every theoretical claim is equally good or that every unobservable claim is false.^[ref]