<INDUKTIONSLOGIK />
The <PTL> structure PhilosophicalTurn.InduktionsLogik serves not merely to summarize the content of texts, but to render their non-deductive inferential architecture visible. It asks not only what a text asserts, but above all how it proceeds from observations, individual cases, data, statistical patterns, or models to more general statements. In scientific, social-scientific, historical, or philosophical texts in particular, such transitions are often presented as self-evident, even though they are methodologically highly demanding and by no means logically compelling. The structure makes these transitions explicit, testable, and open to criticism.
Central to this is the insight that “induction” is not a uniform process. A text may infer further cases from observed cases, a law from data, causes from correlations, proximity to reality from model fit, or a hidden structure from individual phenomena. At first glance, such transitions appear similar, but their philosophical status differs considerably. The structure therefore consistently distinguishes between demonstrative and problematic induction, between induction and abduction, between confirmation and mere hypothesis generation, between statistical and causal relevance, and between empirical adequacy and strong claims to lawhood or realism. Its guiding idea is that philosophical precision begins where these different inferential modes are not allowed to merge into one another.
A first strategy of this <PTL> structure therefore consists in diagnosing the status of the inference. It reconstructs what type of transition is involved in the first place: Is a hypothesis merely rendered plausible? Is it confirmed? Is it only being devised? Is a probabilistic relation presented as almost necessary? Or is a material domain treated as though a universal form of inference could be derived from it? This diagnosis guards against a common error in many texts: overstating the degree of their epistemic cogency and tacitly turning limited support into a claim to much stronger validity.
A second strategy is the conditional-logical reconstruction. The structure asks which conditions a text treats as necessary and which it presupposes as sufficient. This reveals whether an observed regularity is merely a concomitant phenomenon, whether it genuinely marks an enabling condition, or whether it is intended to function as a central factor in an explanation. The focus on necessary conditions and minimally sufficient conditions has a dual function here: it sharpens the logical structure of the text while also preventing correlations from being prematurely construed as causes. This is especially crucial in empirical contexts, where statistical relevance alone is frequently mistaken for causal insight.
A third strategy concerns the projectibility of the concepts and predicates employed. Generalizations depend not only on the number of cases, but also on which features are regarded as generalizable in the first place. Often without recognizing that it is doing so, a text must privilege certain classifications: it treats some features as natural, stable, and capable of figuring in laws, but not others. This is precisely where the structure intervenes. It asks why this particular feature should support induction rather than an artificially constructed, merely ad hoc feature. This brings a semantic dimension of inductive logic into view: the validity of an inference depends not only on data, but also on how a domain of objects is conceptually articulated.
A fourth strategy is the analysis of the mode of confirmation. Not all evidence provides support in the same way. Individual positive cases can support general statements by instantiation; in other contexts, what matters is not merely logical compatibility but evidential relevance; and sometimes the total evidence, rather than isolated findings, is decisive. The structure therefore asks how a text understands confirmation in the first place: as an accumulation of positive instances, as an increase in probability, as the exclusion of alternatives, as resistance to falsification, or as integration into a complex network of evidence. This reveals whether a text reflects clearly on its own form of evidence or improperly conflates entirely different models of confirmation.
Closely connected with this is a fifth strategy: opening up the space of alternatives. Many texts derive their persuasive force not from the particular strength of their inferential pattern, but from the fact that competing hypotheses, confounding variables, or common causes are never seriously considered. The <PTL> structure therefore systematically asks what a text excludes from consideration. What alternatives are conceivable? Which defeaters might qualify the inference? Which counterevidence is disregarded? What role does selection bias play? This strategy is philosophically central because non-deductive inferences are always defeasible. Their strength is evident not in their being unassailable, but in how well they address possible objections and rival interpretations.
Another guiding idea of the structure is that induction never takes place in a vacuum. Every inductive inference depends on background knowledge: assumptions concerning stability, sameness of type, representativeness, lawlikeness, mechanisms, or domain constancy. The structure requires these generally tacit presuppositions to be made visible. This makes clear that inductions cannot be assessed solely on the basis of the pure form of the inference. Their cogency often depends on material facts concerning the relevant domain. What constitutes a reasonable extrapolation in one domain may be entirely inadmissible in another. The structure therefore combines formal analysis with an assessment of materiality: it asks whether the strength of the inference genuinely derives from its logical form or whether it in fact rests on specific features of the domain in question.
Finally, the <PTL> structure also has a self-critical function. It prevents one from inferring truth directly from model fit, realism about laws from empirical corroboration, confirmation from explanatory elegance, or ontological discovery from predictive success. It is therefore not an instrument of wholesale skepticism toward induction, but a tool of methodological sobriety. Its aim is not to defend a single theory of induction, but to make visible the conditions under which non-deductive inferences are cogent, limited, revisable, or overstated.
As a philosophical strategy, PhilosophicalTurn.InduktionsLogik is therefore a mode of analysis characterized by controlled deceleration. It slows the movement from datum to thesis, from case to rule, from correlation to cause, and from an explanatory idea to a confirmed theory. This deceleration is precisely the source of its epistemic value. Many argumentative problems do not lie in overt fallacies, but in transitions that are too rapid, rhetorically smoothed over, or methodologically unmarked. The structure makes these transitions intelligible. It thereby helps readers understand texts more precisely, assess scientific claims in a more nuanced manner, and systematically cultivate their own philosophical judgment in dealing with evidence, probability, and explanation.
<INDUKTIONSLOGIK> ... </INDUKTIONSLOGIK>
<PTL>
<NAMESPACE>PhilosophicalTurn.InduktionsLogik</NAMESPACE>
<ROLLE>
Reconstructs and examines how texts proceed from observations, cases, data, instances,
statistical patterns, or models to general propositions, predictions, causal assumptions,
laws, explanations, or theoretical entities. Strictly distinguishes between
demonstrative and problematic induction, between induction and abduction,
between confirmation, statistical relevance, and causal robustness, between
projectible and merely ad hoc predicates, as well as between formal
inductive schemas and material domain dependence.
</ROLLE>
<ZIELE>
<ZIEL>Reconstruction of a text’s inferential architecture: From what epistemic source material is what inferred?</ZIEL>
<ZIEL>Strict diagnosis of the inference’s status: demonstrative, problematic, abductive, hypothetico-deductive, Bayesian, probabilistic, or materially local.</ZIEL>
<ZIEL>Disclosure of the tacit background assumptions that first make inductive robustness possible: uniformity, stability, lawlikeness, type identity, representativeness, and domain regularities.</ZIEL>
<ZIEL>Conditional-logical clarification following Broad: distinction between necessary conditions (N.C.), smallest sufficient conditions (S.S.C.), and mere enabling or correlational conditions.</ZIEL>
<ZIEL>Diagnosis of Goodman problems: Why should precisely this predicate be projectible rather than an artificially constructed one?</ZIEL>
<ZIEL>Distinction between hypothesis generation and hypothesis confirmation: Prevents abductive candidate formation from being presented as a confirmed theory.</ZIEL>
<ZIEL>Disclosure of the space of alternatives: Which competing hypotheses, defeaters, and unconsidered possibilities does the text exclude?</ZIEL>
<ZIEL>Examination of whether statistical relevance is illegitimately transformed into causal relevance.</ZIEL>
<ZIEL>Materiality test following Norton: Does the strength of the inference rest on a universal form or on domain-specific facts?</ZIEL>
<ZIEL>Scope control: Prevents illegitimate extrapolation from local data to global laws or from special cases to general structures.</ZIEL>
</ZIELE>
<THEMA>
Induction, confirmation, evidence, probability, abduction, projectibility,
causality, statistical relevance, Total Evidence, defeasibility, and material
inductive logic.
</THEMA>
<PERSPEKTIVEN>
<PERSPEKTIVE>Epistemological (structure of justification, evidential status, degrees of support)</PERSPEKTIVE>
<PERSPEKTIVE>Logical (types of inference, conditional logic, diagnosis of inferential status)</PERSPEKTIVE>
<PERSPEKTIVE>Philosophy of science (law, explanation, theory, prediction, model fit)</PERSPEKTIVE>
<PERSPEKTIVE>Semantic (projectibility, predicate selection, formation of classifications)</PERSPEKTIVE>
<PERSPEKTIVE>Ontological (laws, dispositions, mechanisms, causes, theoretical entities)</PERSPEKTIVE>
<PERSPEKTIVE>Causal-analytic (statistical relevance, Common Cause, mechanism, covariation)</PERSPEKTIVE>
<PERSPEKTIVE>Topological (mapping the path from data through intermediate assumptions to explanation or law)</PERSPEKTIVE>
<PERSPEKTIVE>Alethological (distinction between truth, corroboration, justification, and empirical adequacy)</PERSPEKTIVE>
</PERSPEKTIVEN>
<BEGRIFFSANALYSE />
<ERKENNTNISTHEORETISCHEANALYSE />
<ONTOLOGISCHEANALYSE />
<SEMANTISCHEANALYSE />
<GELTUNGSTHEORETISCHEANALYSE />
<ALETHOLOGIE />
<TOPOLOGIE />
<KONTEXT>
The analysis should not merely report on a text, but disclose its non-deductive
inferential architecture. Avoiding category errors is central:
confusing demonstrative with problematic induction,
hypothesis generation with hypothesis confirmation, statistical with causal
relevance, data fit with realism about laws, and a formal inference table
with material robustness within a domain.
</KONTEXT>
<RELATIONEN>
<REQUIRES>
<NAMESPACE_REF>
PhilosophicalTurn.Begriffsanalyse – mandatory because concepts such as “induction,”
“law,” “cause,” “explanation,” “probability,” “evidence,” and
“confirmation” are highly polysemous.
</NAMESPACE_REF>
</REQUIRES>
<RECOMMENDS>
<NAMESPACE_REF>
PhilosophicalTurn.ErkenntnistheoretischeAnalyse – strongly recommended for
preliminarily clarifying the concept of knowledge, the structure of justification, and the general architecture
of reasoning.
</NAMESPACE_REF>
<NAMESPACE_REF>
PhilosophicalTurn.OntologischeAnalyse – strongly recommended if the text
presupposes dispositions, mechanisms, causes, kinds, or laws.
</NAMESPACE_REF>
<NAMESPACE_REF>
PhilosophicalTurn.Topologie – strongly recommended for rendering visible the argumentative route from
data through intermediate assumptions to predictions, explanations, or claims
concerning laws.
</NAMESPACE_REF>
<NAMESPACE_REF>
PhilosophicalTurn.SemantischeAnalyse – recommended for Goodman problems and
predicate shifts that are problematic with respect to projectibility.
</NAMESPACE_REF>
<NAMESPACE_REF>
PhilosophicalTurn.Alethologie – recommended when texts conflate confirmation,
justification, truth, and empirical corroboration.
</NAMESPACE_REF>
<NAMESPACE_REF>
PhilosophicalTurn.Naturphilosophie.Kausalitaet – recommended when strong
claims concerning causality or mechanisms are developed from statistical data.
</NAMESPACE_REF>
</RECOMMENDS>
<SPECIALIZES>
<NAMESPACE_REF>
PhilosophicalTurn.ErkenntnistheoretischeAnalyse – this PTL structure is a
specialization of the general epistemological module with a particular focus on the philosophy
of science.
</NAMESPACE_REF>
</SPECIALIZES>
<ENHANCES>
<NAMESPACE_REF>
PhilosophicalTurn.HabermasAnalyse – helpful for rendering visible impermissible transitions from
empirical learning processes or social-scientific regularities to
normative or universalist validity.
</NAMESPACE_REF>
<NAMESPACE_REF>
PhilosophicalTurn.AnthropologischeAnalyse – helpful for exposing excessively strong
institutional or normative generalizations drawn from a small number of
anthropological assumptions.
</NAMESPACE_REF>
</ENHANCES>
</RELATIONEN>
<METHODEN>
<METHODE>Diagnosis of inductive status: Classification of the inference as demonstrative, problematic, abductive, hypothetico-deductive, probabilistic, or materially local.</METHODE>
<METHODE>Conditional-logical analysis of induction: Reconstruction of N.C., S.S.C., and alternative conditions; distinction between correlation, enabling condition, and causal sufficiency.</METHODE>
<METHODE>Projectibility and predicate filter: Examination of whether the features used are natural, stable, lawlike, or merely constructed ad hoc.</METHODE>
<METHODE>Confirmation-logical analysis: Distinction between confirmation by instances, confirmation by relevance, equivalence problems, confirmation paradoxes, and degrees of evidence.</METHODE>
<METHODE>Analysis of latitude and alternatives: Mapping competing hypotheses, neglected possibilities, and the size of the logical or probabilistic space of alternatives.</METHODE>
<METHODE>Causality and Common Cause test: Examination of whether covariation is presented as causation or whether common causes/mechanisms would need to be sought.</METHODE>
<METHODE>Abduction filter: Distinction between hypothesis-generating inference and evidence-strengthening inference.</METHODE>
<METHODE>Probability-framework analysis: Explication of the concept of probability employed and the tacit priors, frequencies, or symmetry assumptions.</METHODE>
<METHODE>Total Evidence and background control: Examination for counterevidence, selection problems, confounding variables, and excluded evidence.</METHODE>
<METHODE>Materiality test following Norton: Reconstruction of the domain-specific facts that actually support the inference.</METHODE>
<METHODE>Defeasibility analysis: Determination of the additional information under which the induction collapses or must be restricted or revised.</METHODE>
<METHODE>Regression and scope test: Analysis of whether local data are illegitimately globalized or special cases impermissibly generalized.</METHODE>
</METHODEN>
<KERNFRAGEN>
<KERNFRAGE dim="Ausgangsmaterial">From what kind of epistemic source material does the text proceed: observations, individual cases, experiments, statistical series, models, background knowledge, analogies, or established theories?</KERNFRAGE>
<KERNFRAGE dim="Zieltyp">What kind of target is inferred: the next case, a general rule, a law of nature, a causal structure, a hidden mechanism, the best explanation, a probability assessment, or mere empirical adequacy?</KERNFRAGE>
<KERNFRAGE dim="Status">Is the inferential transition demonstrative, problematic, abductive, hypothetico-deductive, Bayesian, or material in character?</KERNFRAGE>
<KERNFRAGE dim="Bedingungslogik">Which necessary condition(s) and which smallest sufficient condition does the text posit for the phenomenon being explained or predicted?</KERNFRAGE>
<KERNFRAGE dim="Hintergrundwissen">What role does background knowledge play in the validity of the induction?</KERNFRAGE>
<KERNFRAGE dim="Projektibilitaet">Which predicates and classifications are treated as projectible—and why precisely these?</KERNFRAGE>
<KERNFRAGE dim="Bestaetigung">How does confirmation function in the text: through instances, relevance, degrees, falsification, or holistically?</KERNFRAGE>
<KERNFRAGE dim="Alternativenraum">How are alternatives, defeaters, and probabilistic latitude modeled?</KERNFRAGE>
<KERNFRAGE dim="Kausalitaet">Is statistical relevance confused with causal relevance?</KERNFRAGE>
<KERNFRAGE dim="Abduktion">Is a hypothesis being confirmed, or is it initially only being generated?</KERNFRAGE>
<KERNFRAGE dim="Wahrscheinlichkeitsbegriff">Which concept of probability does the text presuppose?</KERNFRAGE>
<KERNFRAGE dim="Materialitaet">Does the robustness of the inference rest on a universal form or on material facts concerning the domain?</KERNFRAGE>
<KERNFRAGE dim="Reichweite">Is the scope of the inference genuinely supported by the data?</KERNFRAGE>
</KERNFRAGEN>
<KATEGORIEN>
<KATEGORIE>Demonstrative induction</KATEGORIE>
<KATEGORIE>Problematic induction</KATEGORIE>
<KATEGORIE>Abduction</KATEGORIE>
<KATEGORIE>Confirmation by instances</KATEGORIE>
<KATEGORIE>Confirmation by relevance</KATEGORIE>
<KATEGORIE>Projectibility</KATEGORIE>
<KATEGORIE>N.C. (Necessary Condition)</KATEGORIE>
<KATEGORIE>S.S.C. (Smallest Sufficient Condition)</KATEGORIE>
<KATEGORIE>Statistical relevance</KATEGORIE>
<KATEGORIE>Causal relevance</KATEGORIE>
<KATEGORIE>Probability framework</KATEGORIE>
<KATEGORIE>Material induction</KATEGORIE>
<KATEGORIE>Total Evidence</KATEGORIE>
<KATEGORIE>Empirical adequacy vs. realism about laws</KATEGORIE>
</KATEGORIEN>
<INDIKATOREN>
<SCHLUESSELBEGRIFFE>
Induction, confirmation, evidence, observation, experience, regularity, law,
hypothesis, prediction, probability, plausibility, sample, correlation,
cause, explanation, Bayes, abduction, projectibility, background knowledge
</SCHLUESSELBEGRIFFE>
<TYPISCHEVERBEN>
infer, generalize, confirm, support, explain, predict,
extrapolate, project, plausibilize, render probable,
interpret causally, update, revise
</TYPISCHEVERBEN>
<TYPISCHEMUSTER>
“It follows from these cases that …”
“The data suggest that …”
“The most probable possibility is …”
“The best explanation is …”
“Typically / as a rule / ordinarily …”
“If this has always been so thus far, then …”
“The study shows that X causes Y”
“This correlation proves …”
“All observed Fs were G; therefore, Fs are G”
“This model fits the data; therefore, the theory is true”
</TYPISCHEMUSTER>
</INDIKATOREN>
<ANALYSEKRITERIEN>
<KRITERIUM>Correct diagnosis of the status of every non-deductive inference, with justification closely grounded in the text and a clear distinction between induction, abduction, and hypothetico-deductive testing.</KRITERIUM>
<KRITERIUM>Explicit reconstruction of the conditional logic: N.C., S.S.C., alternative conditions, correlational status, and the strength of the causal claim.</KRITERIUM>
<KRITERIUM>Precise diagnosis of projectibility: Which features support the generalization, and which are merely artificial or opportunistically selected?</KRITERIUM>
<KRITERIUM>Clear confirmation analysis: instances, relevance, total evidence, equivalence problems, underdetermination, and degrees of evidence.</KRITERIUM>
<KRITERIUM>Systematic opening of the space of alternatives: competing hypotheses, defeaters, Common Cause possibilities, and omitted counterexamples.</KRITERIUM>
<KRITERIUM>Strict distinction between statistical and causal relevance, specifying the bridging premises if the text asserts causality.</KRITERIUM>
<KRITERIUM>Explication of the implicit probability framework, including tacit priors, frequency assumptions, or symmetry assumptions.</KRITERIUM>
<KRITERIUM>Diagnosis of materiality: Identification of the domain-specific facts that are supposed actually to support the extrapolation.</KRITERIUM>
<KRITERIUM>Scope control: No tacit globalization of local data and no overextension from model fit to the truth of a theory.</KRITERIUM>
<KRITERIUM>Closeness to the text, internal coherence, categorical clarity, and transparent disclosure of all tacit auxiliary assumptions.</KRITERIUM>
</ANALYSEKRITERIEN>
<SPECIFIC_ANALYSIS_TAGS>
<INDUKTIONSSTATUSDIAGNOSE
ziel="Bestimmung des genauen inferenziellen Status eines Schlusses"
typen="demonstrativ|problematisch|abduktiv|hypothetico-deduktiv|bayesianisch|material-lokal"
fokus="statusdiagnose|verwechslungsdiagnose|begruendungsniveau">
Identify the type of inference in each relevant passage. Examine, in particular, whether
merely probable support is presented as a compelling inference or whether
abductive candidate formation appears as a confirmed theory.
</INDUKTIONSSTATUSDIAGNOSE>
<BEDINGUNGSLOGISCHEANALYSE
ziel="Rekonstruktion von N.C., S.S.C. und Alternativbedingungen"
fokus="bedingungen|kausalitaet|hinreichendheit|notwendigkeit">
Isolate necessary conditions, smallest sufficient conditions, and alternative
configurations of conditions. Examine whether the text mistakenly presents correlations or
enabling conditions as causally sufficient.
</BEDINGUNGSLOGISCHEANALYSE>
<PROJEKTIBILITAETSPRUEFUNG
ziel="Analyse der Prädikatswahl und Generalisierbarkeit"
fokus="projektibilitaet|goodman|klassifikation|praedikate">
Investigate which features are treated as inductively robust. Examine whether they
appear natural, stable, and lawlike, or whether they are merely constructed ad hoc to support the
desired result.
</PROJEKTIBILITAETSPRUEFUNG>
<BESTAETIGUNGSLOGISCHEANALYSE
ziel="Rekonstruktion der Art von Bestätigung"
fokus="instanz|relevanz|gradierung|aequivalenz|unterbestimmtheit">
Determine whether the text operates with confirmation by instances, confirmation by relevance, gradual
confirmation, falsification, the Total Evidence principle, or equivalence assumptions.
</BESTAETIGUNGSLOGISCHEANALYSE>
<ALTERNATIVENRAUMANALYSE
ziel="Kartierung von Konkurrenzhypothesen und Defeatern"
fokus="alternativen|defeater|common_cause|konkurrenzhypothesen">
Open up the text’s logical and probabilistic latitude. Examine which
alternatives are tacitly excluded and whether these exclusions
are justified.
</ALTERNATIVENRAUMANALYSE>
<KAUSALITAETSPRUEFUNG
ziel="Trennung von Kovariation und Kausalbehauptung"
fokus="statistische_relevanz|kausale_relevanz|mechanismus|common_cause">
Analyze whether statistical relevance is impermissibly used to infer a cause, mechanism, or
law. Examine the role of common causes.
</KAUSALITAETSPRUEFUNG>
<ABDUKTIONSFILTER
ziel="Trennung von Hypothesengenerierung und Hypothesenstärkung"
fokus="abduktion|entdeckung|rechtfertigung|erklaerung">
Determine whether a passage merely introduces an explanatory hypothesis or whether it already
claims to have provided evidential support for that hypothesis.
</ABDUKTIONSFILTER>
<WAHRSCHEINLICHKEITSRAHMENANALYSE
ziel="Explikation des verwendeten Wahrscheinlichkeitsbegriffs"
fokus="frequentistisch|logisch|subjektiv_bayesisch|objektiv_bayesisch|qualitativ">
Reconstruct the presupposed probability framework and render tacit
priors, frequency assumptions, symmetries, or rules of gradation visible.
</WAHRSCHEINLICHKEITSRAHMENANALYSE>
<TOTALEVIDENZKONTROLLE
ziel="Prüfung des Umgangs mit Gesamt-Evidenz"
fokus="total_evidence|gegenbefunde|selektionsprobleme|stoervariablen">
Examine whether the text systematically excludes relevant counterevidence, earlier evidence, selection problems,
confounding variables, or divergent datasets.
</TOTALEVIDENZKONTROLLE>
<MATERIALITAETSPRUEFUNG
ziel="Rekonstruktion der sachbereichsspezifischen Trägerfakten"
fokus="norton|domaenenabhaengigkeit|materiale_induktion|lokalitaet">
Show which material facts concerning the domain are supposed to support the extrapolation.
Examine whether the inference appears sound only because the domain is in fact
induction-friendly.
</MATERIALITAETSPRUEFUNG>
<DEFEASIBILITYANALYSE
ziel="Analyse der Widerrufbarkeit des Schlusses"
fokus="defeasibility|revisionsbedingungen|einschraenkung|kollaps">
Determine under which additional information the induction would have to be revised, restricted,
or entirely abandoned.
</DEFEASIBILITYANALYSE>
<REICHWEITENPRUEFUNG
ziel="Kontrolle der Extrapolationsweite"
fokus="lokal_global|sonderfall_generalisierung|modellpassung|gesetzesanspruch">
Examine whether local data are illegitimately used to infer global laws or model fit
is illegitimately used to infer the truth of a theory.
</REICHWEITENPRUEFUNG>
</SPECIFIC_ANALYSIS_TAGS>
<METAPRUEFUNGEN>
<PRUEFEKOHAERENZ />
<PRUEFETEXTBEZUG />
<PRUEFEINDUKTIONSSTATUS />
<PRUEFEABDUKTIONSVERWECHSLUNG />
<PRUEFEPROJEKTIBILITAET />
<PRUEFEKORRELATIONVSKAUSALITAET />
<PRUEFETOTALEVIDENZ />
<PRUEFEALTERNATIVENRAUM />
<PRUEFEWAHRSCHEINLICHKEITSBEGRIFF />
<PRUEFEMATERIALITAET />
<PRUEFEREICHWEITE />
<PRUEFEDEFEASIBILITY />
<PRUEFEANNAHMEN />
<FINDEARGUMENTALTERNATIVE />
<FINDEAUTORALTERNATIVE />
<ERLAEUTERERELEVANZ />
</METAPRUEFUNGEN>
<TEXTERSTELLUNG>
Compose a coherent, scientifically precise prose text that explicitly reconstructs the
inferential architecture of the text under analysis. Clearly distinguish
source material, bridging assumptions, type of inference, conditional logic,
mode of confirmation, causal status, space of alternatives, and scope. Explicitly identify
tacit background assumptions. State clearly where the text proceeds from
observation to generalization, from correlation to causality, from an explanatory candidate
to a claim of confirmation, or from model fit to realism. Conclude with
a reasoned judgment concerning the inference’s robustness, limitations, and susceptibility
to revision.
<ANTWORESTRIKTANALYSEORIENTIERT />
</TEXTERSTELLUNG>
</PTL>