I. The Administrative Treatment of Chance

Modern institutions rarely deny the existence of randomness outright. Instead, they approach it administratively. Chance is treated as a variable to be modeled, bounded, insured against, or absorbed into procedure. From actuarial tables and risk scores to performance metrics and governance frameworks, randomness is neither celebrated nor rejected; it is processed.

This processing rests on a crucial assumption: that chance becomes acceptable once it is rendered calculable. When uncertainty can be expressed statistically, distributed across populations, or embedded within standardized procedures, it ceases to appear arbitrary. The outcome may remain contingent, but its contingency is reframed as the byproduct of a rational system. What matters is not that the result could have been otherwise, but that it emerged from a process that can be defended.

In this way, institutions do not eliminate randomness; they translate it into justification. Statistical expectation replaces fortune, procedure replaces luck, and compliance replaces fate. The language of fairness shifts accordingly. Decisions are no longer judged by their outcomes, but by the legitimacy of the process that produced them. If the procedure is sound, the result is presumed fair—even when its effects are starkly unequal.

This translation has a stabilizing function. By embedding chance within layers of method and expertise, institutions protect themselves from accusations of arbitrariness. Randomness does not disappear; it is displaced upward, away from outcomes and into design. What appears at the surface as merit, optimization, or due process often conceals a deeper dependence on contingent factors that remain unacknowledged.

The result is a peculiar asymmetry. When outcomes favor those already advantaged, their contingency is rarely questioned. When outcomes appear unjust, the appeal is not to chance, but to reform: better metrics, improved models, refined governance. Randomness is tolerated only insofar as it remains invisible. Once exposed, it is treated as a failure of administration rather than a structural condition.

This logic explains why explicit mechanisms of chance—lotteries, draws, or random allocation—are widely regarded as unfair by default, even when they distribute outcomes evenly. Their fault is not inefficiency, but transparency. They make visible what most systems work to obscure: that many decisive outcomes are not earned, optimized, or deserved, but simply occur.

II. Deserved Outcomes and the Refusal of Contingency

The administrative management of chance would be unremarkable if it remained a technical matter. Its deeper significance lies elsewhere: in how it reshapes the way outcomes are interpreted and justified. Once randomness is embedded within procedure, results are no longer merely contingent; they acquire moral meaning. What emerges is not just inequality, but deserved inequality.

Modern societies exhibit a marked discomfort with outcomes that lack justification. An event that happens without reason—a sudden gain, an unearned loss, an arbitrary allocation—demands explanation. If none is available, it is experienced as intolerable. The response is rarely to accept contingency as such, but to retroactively supply reasons: effort, merit, risk-taking, compliance, or failure to adapt. Randomness is not denied; it is converted into narrative.

This conversion is not accidental. It performs a crucial psychological and social function. Systems that present outcomes as deserved stabilize expectations and diffuse resentment. They allow individuals to interpret their position—favorable or not—as meaningful rather than accidental. In doing so, they protect institutions from the corrosive effects of visible arbitrariness. A system that produces unequal outcomes without explanation invites challenge; a system that produces them with reasons invites resignation.

The moralization of outcomes thus depends on a selective blindness to contingency. While chance continues to operate at every level—birth, opportunity, timing, exposure—it is acknowledged only when it can be neutralized. Success is attributed to agency; failure is attributed to deficit. The underlying randomness that conditions both remains structurally unaddressed.

This asymmetry reveals a deeper anthropological tension. Humans are capable of accepting randomness in domains where justification is impossible or irrelevant: natural disasters, genetic variation, mortality. But where outcomes intersect with status, wealth, or recognition, contingency becomes threatening. It undermines the narratives through which social hierarchies are rendered legitimate. To accept randomness openly in these domains would be to admit that many decisive differences lack reason altogether.

For this reason, systems that expose contingency too clearly provoke discomfort or rejection. A lottery that distributes resources evenly may appear fair in outcome, yet unjust in principle, because it refuses to explain itself. It offers no account of why one individual receives more than another. Its indifference is experienced not as neutrality, but as abdication. What is rejected, in such cases, is not inequality, but the absence of justification.

This reaction clarifies what is at stake. Fairness, as it is commonly understood, is less concerned with equality than with intelligibility. Outcomes must be readable as the result of something—effort, procedure, optimization—even when the explanatory link is tenuous. Randomness becomes unacceptable not because it produces bad results, but because it produces results without meaning.

III. The Exhaustion of Justification

If modern institutions devote such effort to explaining outcomes, it is because justification has become their primary mode of legitimacy. Decisions need not be optimal, nor even beneficial, provided they can be rendered intelligible within an accepted framework. What matters is not that an outcome is good, but that it can be explained without remainder.

This reliance on justification, however, encounters a structural limit. The more systems attempt to account for outcomes through layered procedures, metrics, and rationales, the more fragile those accounts become. Each additional explanation introduces new assumptions, new contingencies, and new points of contestation. Justification proliferates, but conviction does not deepen.

At a certain point, explanation ceases to reassure. When outcomes are repeatedly defended through increasingly complex narratives of optimization, responsibility, or necessity, they begin to appear less grounded, not more. What was meant to neutralize arbitrariness instead multiplies its traces. The system speaks more, but says less.

This exhaustion is most visible where stakes are highest. In domains such as wealth distribution, access to opportunity, or political authority, justificatory frameworks are constantly revised, refined, and recalibrated. Yet dissatisfaction persists. The problem is not merely that explanations are insufficient, but that no explanation can fully absorb the role of contingency without undermining itself. To acknowledge chance openly would invalidate the claim that outcomes are deserved; to deny it entirely would strain credibility beyond repair.

As a result, justification enters a defensive posture. It no longer seeks to convince, but to close debate. Procedures are invoked not as reasons, but as endpoints. Decisions are declared final because they followed the rules, even when the rules themselves are opaque or unstable. What remains is a thin legitimacy, maintained through repetition rather than persuasion.

This condition reveals a deeper impasse. Justification presupposes that outcomes can, in principle, be made meaningful. Randomness resists this presupposition. It produces results without reasons, distributions without narratives, differences without grounds. Where randomness is structurally present, justification can only ever be partial, provisional, or retrospective.

The attempt to fully justify outcomes in such conditions is therefore self-defeating. Either contingency is acknowledged, in which case justification loses its authority, or it is concealed, in which case justification becomes suspect. In both cases, the promise that fairness can be secured through explanation alone proves untenable.

What emerges is not a failure of specific institutions, but a general limit. Justification can organize acceptance, but it cannot eliminate the discomfort produced by outcomes that lack meaning. At best, it delays confrontation with contingency. At worst, it transforms that contingency into moral judgment, binding individuals to outcomes they are told to have earned, even when the grounds remain uncertain.

Conclusion

The concealment of chance is not a technical failure, nor a temporary misalignment between ideals and outcomes. It is a structural response to a problem that cannot be resolved: the demand that outcomes be both contingent and justified, unequal and meaningful. Modern institutions manage this tension by translating randomness into procedure and contingency into desert, sustaining the appearance of fairness while avoiding direct confrontation with arbitrariness. What this strategy ultimately reveals is not a deficit of explanation, but its limit. Where chance remains operative, justification can organize acceptance but not eliminate unease. The insistence on explaining outcomes, rather than acknowledging contingency, thus marks less a triumph of rationality than a refusal—quiet, systematic, and enduring—to accept the role of chance in the distribution of lives.

I. The Administrative Treatment of Chance

Modern institutions rarely deny the existence of randomness outright. Instead, they approach it administratively. Chance is treated as a variable to be modeled, bounded, insured against, or absorbed into procedure. From actuarial tables and risk scores to performance metrics and governance frameworks, randomness is neither celebrated nor rejected; it is processed.

This processing rests on a crucial assumption: that chance becomes acceptable once it is rendered calculable. When uncertainty can be expressed statistically, distributed across populations, or embedded within standardized procedures, it ceases to appear arbitrary. The outcome may remain contingent, but its contingency is reframed as the byproduct of a rational system. What matters is not that the result could have been otherwise, but that it emerged from a process that can be defended.

In this way, institutions do not eliminate randomness; they translate it into justification. Statistical expectation replaces fortune, procedure replaces luck, and compliance replaces fate. The language of fairness shifts accordingly. Decisions are no longer judged by their outcomes, but by the legitimacy of the process that produced them. If the procedure is sound, the result is presumed fair—even when its effects are starkly unequal.

This translation has a stabilizing function. By embedding chance within layers of method and expertise, institutions protect themselves from accusations of arbitrariness. Randomness does not disappear; it is displaced upward, away from outcomes and into design. What appears at the surface as merit, optimization, or due process often conceals a deeper dependence on contingent factors that remain unacknowledged.

The result is a peculiar asymmetry. When outcomes favor those already advantaged, their contingency is rarely questioned. When outcomes appear unjust, the appeal is not to chance, but to reform: better metrics, improved models, refined governance. Randomness is tolerated only insofar as it remains invisible. Once exposed, it is treated as a failure of administration rather than a structural condition.

This logic explains why explicit mechanisms of chance—lotteries, draws, or random allocation—are widely regarded as unfair by default, even when they distribute outcomes evenly. Their fault is not inefficiency, but transparency. They make visible what most systems work to obscure: that many decisive outcomes are not earned, optimized, or deserved, but simply occur.

II. Deserved Outcomes and the Refusal of Contingency

The administrative management of chance would be unremarkable if it remained a technical matter. Its deeper significance lies elsewhere: in how it reshapes the way outcomes are interpreted and justified. Once randomness is embedded within procedure, results are no longer merely contingent; they acquire moral meaning. What emerges is not just inequality, but deserved inequality.

Modern societies exhibit a marked discomfort with outcomes that lack justification. An event that happens without reason—a sudden gain, an unearned loss, an arbitrary allocation—demands explanation. If none is available, it is experienced as intolerable. The response is rarely to accept contingency as such, but to retroactively supply reasons: effort, merit, risk-taking, compliance, or failure to adapt. Randomness is not denied; it is converted into narrative.

This conversion is not accidental. It performs a crucial psychological and social function. Systems that present outcomes as deserved stabilize expectations and diffuse resentment. They allow individuals to interpret their position—favorable or not—as meaningful rather than accidental. In doing so, they protect institutions from the corrosive effects of visible arbitrariness. A system that produces unequal outcomes without explanation invites challenge; a system that produces them with reasons invites resignation.

The moralization of outcomes thus depends on a selective blindness to contingency. While chance continues to operate at every level—birth, opportunity, timing, exposure—it is acknowledged only when it can be neutralized. Success is attributed to agency; failure is attributed to deficit. The underlying randomness that conditions both remains structurally unaddressed.

This asymmetry reveals a deeper anthropological tension. Humans are capable of accepting randomness in domains where justification is impossible or irrelevant: natural disasters, genetic variation, mortality. But where outcomes intersect with status, wealth, or recognition, contingency becomes threatening. It undermines the narratives through which social hierarchies are rendered legitimate. To accept randomness openly in these domains would be to admit that many decisive differences lack reason altogether.

For this reason, systems that expose contingency too clearly provoke discomfort or rejection. A lottery that distributes resources evenly may appear fair in outcome, yet unjust in principle, because it refuses to explain itself. It offers no account of why one individual receives more than another. Its indifference is experienced not as neutrality, but as abdication. What is rejected, in such cases, is not inequality, but the absence of justification.

This reaction clarifies what is at stake. Fairness, as it is commonly understood, is less concerned with equality than with intelligibility. Outcomes must be readable as the result of something—effort, procedure, optimization—even when the explanatory link is tenuous. Randomness becomes unacceptable not because it produces bad results, but because it produces results without meaning.

III. The Exhaustion of Justification

If modern institutions devote such effort to explaining outcomes, it is because justification has become their primary mode of legitimacy. Decisions need not be optimal, nor even beneficial, provided they can be rendered intelligible within an accepted framework. What matters is not that an outcome is good, but that it can be explained without remainder.

This reliance on justification, however, encounters a structural limit. The more systems attempt to account for outcomes through layered procedures, metrics, and rationales, the more fragile those accounts become. Each additional explanation introduces new assumptions, new contingencies, and new points of contestation. Justification proliferates, but conviction does not deepen.

At a certain point, explanation ceases to reassure. When outcomes are repeatedly defended through increasingly complex narratives of optimization, responsibility, or necessity, they begin to appear less grounded, not more. What was meant to neutralize arbitrariness instead multiplies its traces. The system speaks more, but says less.

This exhaustion is most visible where stakes are highest. In domains such as wealth distribution, access to opportunity, or political authority, justificatory frameworks are constantly revised, refined, and recalibrated. Yet dissatisfaction persists. The problem is not merely that explanations are insufficient, but that no explanation can fully absorb the role of contingency without undermining itself. To acknowledge chance openly would invalidate the claim that outcomes are deserved; to deny it entirely would strain credibility beyond repair.

As a result, justification enters a defensive posture. It no longer seeks to convince, but to close debate. Procedures are invoked not as reasons, but as endpoints. Decisions are declared final because they followed the rules, even when the rules themselves are opaque or unstable. What remains is a thin legitimacy, maintained through repetition rather than persuasion.

This condition reveals a deeper impasse. Justification presupposes that outcomes can, in principle, be made meaningful. Randomness resists this presupposition. It produces results without reasons, distributions without narratives, differences without grounds. Where randomness is structurally present, justification can only ever be partial, provisional, or retrospective.

The attempt to fully justify outcomes in such conditions is therefore self-defeating. Either contingency is acknowledged, in which case justification loses its authority, or it is concealed, in which case justification becomes suspect. In both cases, the promise that fairness can be secured through explanation alone proves untenable.

What emerges is not a failure of specific institutions, but a general limit. Justification can organize acceptance, but it cannot eliminate the discomfort produced by outcomes that lack meaning. At best, it delays confrontation with contingency. At worst, it transforms that contingency into moral judgment, binding individuals to outcomes they are told to have earned, even when the grounds remain uncertain.

Conclusion

The concealment of chance is not a technical failure, nor a temporary misalignment between ideals and outcomes. It is a structural response to a problem that cannot be resolved: the demand that outcomes be both contingent and justified, unequal and meaningful. Modern institutions manage this tension by translating randomness into procedure and contingency into desert, sustaining the appearance of fairness while avoiding direct confrontation with arbitrariness. What this strategy ultimately reveals is not a deficit of explanation, but its limit. Where chance remains operative, justification can organize acceptance but not eliminate unease. The insistence on explaining outcomes, rather than acknowledging contingency, thus marks less a triumph of rationality than a refusal—quiet, systematic, and enduring—to accept the role of chance in the distribution of lives.