= Solution
\b[A plausible demarcation assesses how a practice makes and tests empirical claims, while allowing unsettled boundary cases.] An exact sentence-level test is less defensible than an account of sustained accountability to evidence. <Pseudoscience> should also be distinguished from honest scientific error and from activities that make no scientific pretension.
<Karl Popper>'s <falsifiability> criterion identifies something central: an empirical theory excludes possible observations. A proposed relation between a controllable input and an instrument reading is testable only if some readings would conflict with it under the stated conditions. Collecting agreeable anecdotes is weak when an account can be made compatible with every outcome. Risky predictions matter because passing a test should have been difficult for a mistaken account.<Science: Conjectures and Refutations by Karl Popper>[chapter 1, section I, numbered conclusions concerning risky prediction, refutability and protective modifications]{ref}
Yet <falsifiability> is not sufficient for good science. Someone could guess tomorrow's detector count and then advertise the guess as an established result. The numerical claim is falsifiable, but that does not supply calibration, a justified sampling model or a reliable research practice. Conversely, an investigation can be scientific even if the working model later proves false. The <demarcation problem> concerns the character of inquiry, not a guarantee of truth.
Nor does a failed prediction always justify immediate rejection of the principal theory. In a test represented by $T\land A\Rightarrow E$, the observation $\neg E$ yields $\neg T\lor\neg A$. The <auxiliary hypotheses> $A$ might include an initial condition, an instrument model or the composition of a sample. This <Duhem problem> is a logical limitation on what one unsuccessful test establishes.<The Aim and Structure of Physical Theory by Pierre Duhem>[part II, chapter VI, section 2, testing a theoretical group rather than a hypothesis in isolation]{ref}
There is nevertheless an evidential difference between a justified repair and an evasive one. If a suspected detector defect is measured independently, and correcting it yields further successful predictions, the change increases the theory's exposure to testing. If a new invisible influence is introduced after each failure with no independent consequences, the repair preserves agreement at the expense of accountability. An <auxiliary hypothesis> is not disreputable merely because it is auxiliary; its evidential role matters.
<Imre Lakatos> therefore shifts attention to sequences of theories and their capacity to generate corroborated new results. A programme that repeatedly anticipates discoveries differs from one that continually explains away known failures.<Science and Pseudoscience by Imre Lakatos>[discussion contrasting progressive and degenerating research programmes]{ref} This improves on judging an isolated claim, but it does not provide a timetable stating exactly how long an initially unsuccessful programme deserves support. New research may need time, and a previously fruitful programme can stagnate.
A workable standard consequently asks whether investigators specify discriminating predictions or comparisons, expose their methods and data to appropriate scrutiny, respond to contrary findings, and seek independent checks. These demands should fit the field. An astronomical claim can be tested by predicted observations and independent instruments even when the investigator cannot manipulate a <star>. A laboratory science can often use controlled interventions. Requiring all inquiry to copy one laboratory format would exclude legitimate evidence.
An objection is that these standards describe good scientific conduct rather than draw an exact boundary. That is partly right. But a usable demarcation need not be a mechanical classifier for every new idea. Persistent evasion of the standards while claiming scientific authority supports a judgement of <pseudoscience>; mixed or immature cases can remain unresolved. A single statistical mistake need not condemn an entire field, while a consistent refusal to acknowledge tests can.
The resulting distinction is plausible because it explains what the boundary is for: identifying practices that can correct error through public evidence. It permits criticism of established institutions as well as marginal claimants. Its price is contextual judgement, which is preferable to pretending that one syntactic feature settles every case.
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