Hard Problem of Objectivity

The myth of the view from nowhere. True objectivity would require a disembodied, ahistorical, bias-free perspective completely outside the system being observed. This is impossible for humans. Every observation is made by a situated observer with a body, a language, a culture, and a set of prior beliefs. The hard problem is that while we can approach objectivity through methods (blinding, controls, peer review), we can never fully attain it. The ideal of pure objectivity may be a necessary regulative ideal for science and ethics, but it is also a philosophical phantom.

Example: A journalist aims to report "objectively" on a political protest. But their choice of which quotes to feature, which images to show, and even the word "protest" (vs. "riot" or "demonstration") reflects a subjective framework. The hard problem: Striving for objectivity is crucial, but claiming to have achieved it is often a power move—a way of dismissing other perspectives as "subjective" or "biased." True objectivity might be the process of continually acknowledging and correcting for subjectivity, not its elimination. Hard Problem of Objectivity.

by Enkigal January 24, 2026

Objectivity Demarcation Problem

The core challenge in science and philosophy: how to distinguish an objective claim (true independent of observers) from a subjective one (dependent on a point of view). Since all observation is theory-laden and filtered through human senses and instruments, pure objectivity might be an impossible ideal. The "problem" is that every method we create to ensure objectivity (double-blind trials, peer review) is itself a socially constructed process. We demarcate the objective as that which survives these constructed filters, but the line is always provisional.

Example: "Two scientists saw the same data curve. One called it random noise; the other, a significant signal. The Objectivity Demarcation Problem is that their prior beliefs—their subjective 'priors'—dictated where they drew the line. Their argument wasn't about the data, but about where to place the demarcation between objective pattern and subjective illusion. Even statistics, our tool for objectivity, requires a subjective choice: the p-value threshold."

by AbzuInExile February 1, 2026

Objectivity Bias

The mistaken belief that a truly "objective" perspective is possible or necessary for valid knowledge, used to dismiss viewpoints that are explicitly situated, personal, or experiential. It ignores that all observation is theory-laden and all knowers have a position. This bias falsely equates impartiality with truth, often to delegitimize marginalized voices whose "objectivity" has been historically denied by the very systems they critique.

Example: Dismissing a Indigenous community's knowledge about local ecosystem changes because it's "anecdotal" and "not objective science," while privileging sparse satellite data, commits Objectivity Bias. It rejects a deep, situated observational history in favor of a distant, "neutral" measurement that may miss crucial, on-the-ground nuances.

by Dumu The Void February 4, 2026

Fallacy of Arbitrary Objectivity

The logical error of claiming that your perspective is objective while everyone else's is biased, without providing any justification for why your viewpoint deserves the "objective" label. This fallacy is the bedrock of punditry, editorial writing, and conversations with your uncle at Thanksgiving. The person committing it positions themselves as a neutral observer floating above the fray, while everyone else is mired in ideology, emotion, or self-interest. The reality, of course, is that they're just as biased as everyone else—they've just declared their bias to be the center of the universe, which is a very convenient way to never have to examine your own assumptions.

Example: "The pundit committed the fallacy of arbitrary objectivity daily, presenting his conservative opinions as 'common sense' and 'what most Americans think' while describing liberal views as 'ideological' and 'out of touch.' He genuinely believed he was objective, which was the most objective sign that he wasn't."

by Dumu The Void February 15, 2026

Law of Absolute and Relative Objectivity

The principle that objectivity operates in two modes: absolute objectivity (a perspective from nowhere, free of all bias and particularity) and relative objectivity (the best approximation of neutrality achievable within a given context). The law acknowledges that pure objectivity may be an ideal we can approach but never reach—like a horizon that recedes as we advance. Relative objectivity is what we actually achieve: perspectives that are as free as possible from obvious bias, while still being situated in a particular time, place, and culture. The law of absolute and relative objectivity reconciles the aspiration to neutrality with the reality of situatedness.

Law of Absolute and Relative Objectivity Example: "He claimed his news source was 'completely objective.' She invoked the law of absolute and relative objectivity: absolute objectivity is impossible (no view from nowhere), but relative objectivity is achievable (minimizing bias, disclosing perspective). His source had relative objectivity at best; his claim to absolute was the problem. He kept watching anyway, which is what people do."

by Abzugal February 16, 2026

Law of Spectral Objectivity

The principle that objectivity exists on a spectrum between absolute and relative, with infinite gradations and multiple dimensions. Under this law, no perspective is simply objective or subjective—each occupies a position in spectral space defined by its distance from pure bias, its acknowledgment of standpoint, its transparency about methods, its community of verification. The law of spectral objectivity recognizes that objectivity is not a binary property but a continuous quality that can be cultivated, measured, and improved. It's the foundation of methodological humility—the recognition that your objectivity is always partial, always situated, always capable of improvement.

Law of Spectral Objectivity Example: "She evaluated her own research using spectral objectivity, mapping it across dimensions: transparency about methods (high), acknowledgment of biases (medium), community verification (ongoing), distance from funding sources (good). The spectral coordinates showed where her objectivity was strong and where it needed work. She improved her practice not by seeking impossible purity but by moving along the spectrum."

by Abzugal February 16, 2026