@kungfufk
Common Sense =personal Judgments + .......... etc
STATUS: SAMPLE / ILLUSTRATIVE MODEL — NOT EMPIRICALLY VALIDATED
This extends the wave/energy series to a new domain: person-to-person variation in "common sense," how overlapping rule-sets produce a shared social sense, and what happens when a person's sense of self-worth becomes chronically dependent on that shared system rather than using it situationally. It also adds a capacity/processing layer: why social events specifically demand a different kind of cognitive resource than analytical tasks do, and why leaning on analytical processing during a social event tends to backfire. It predicts risk of psychological/relational harm and social performance quality — not truth, virtue, or how any specific person should live. Free parameters are unfit. This is not a diagnostic tool and should never be used to assess a real, named individual.
1. Purpose
The source framework modeled a single person's bounded-rational processing. This document asks two related questions:
- What happens between people, when each person's "common sense" is actually a private rule-set, not a shared universal truth — and what happens when a person leans on the overlap between rule-sets (their social sense) as their main source of self-worth or decision-making, rather than using it situationally, when a specific social function actually requires it (e.g., marriage, group ritual, negotiation)?
- What kind of processing capacity social events actually draw on — and why defaulting to analytical processing during a live social event tends to degrade performance rather than help it.
The core claim, restated plainly: common sense is not one thing — it's each person's internalized rule-set, built from their own knowledge and experience. Where rule-sets overlap across people, you get a shared "social sense." That overlap is a genuinely useful tool for specific social functions. But treating it as a default operating system for private life — rather than a tool you pick up for specific occasions — creates a dependency that can cause real harm. Separately, social events draw on a high-capacity, holistic, "in the moment" mode of processing; leaning on slow, analytical processing during those events tends to produce worse social outcomes, not better ones.
Both halves map onto real, established research, named directly below rather than dressed in new notation.
2. Notation
| Symbol | Meaning |
|---|
| $R_i$ | Person $i$'s common-sense rule-set — their internalized collection of norms, heuristics, and knowledge-based rules |
| $S_{ij}$ | Overlap between person $i$'s and person $j$'s rule-sets — their shared social sense |
| $D_i$ | Person $i$'s social value dependency — how much of their self-worth/decision-weight is anchored to $S$ rather than to private, internally-held values |
| $V(t)$ | Variance/instability of the social rule-set a person is relying on across different groups or contexts |
| $F$ | A specific bounded social function requiring consensus (marriage negotiation, ritual, group coordination) |
| $H_i$ | Predicted harm/injury risk for person $i$ — chronic stress, identity strain, or relational rupture, not physical injury |
| $C_{soc}(t)$ | General social-processing capacity available in the moment — the "holistic energy" a live social event draws on |
| $P_i(t)$ | Processing-mode mix person $i$ is running: how much of their output is social/emotional-ego processing vs. analytical processing, at time $t$ |
3. Assumptions
- Assumption 1 — Common sense is a rule-set, not a universal constant. Each person's "common sense" is built from their own accumulated knowledge, culture, and experience — so two people's rule-sets are overlapping sets, not identical copies. This matches a basic premise in cultural and cognitive sociology: norms are learned and locally variable, not innate or universal.
- Assumption 2 — Overlap, not fusion. Where rule-sets intersect across many people, you get something reasonably called a shared social sense — but it is a set intersection, not a merged single wave. Set/overlap math (e.g., a Jaccard-style overlap coefficient) fits this better than a shared-frequency wave model, so this document deliberately does not reuse the sine-wave formalism from earlier documents here — that borrow would be inappropriate for a discrete, group-membership concept like "shared norms."
- Assumption 3 — Dependency is a dial, not a switch. People vary continuously in how much they anchor self-worth/decisions to $S_{ij}$ (external consensus) vs. private, self-generated values. This is a direct restatement of a real, measured construct: contingent self-worth (Crocker & Wolfe, 2001) — the degree to which someone's self-esteem depends on external approval, appearance, or others' opinions, as opposed to internally held standards.
- Assumption 4 — Function-bound use of consensus is adaptive; generalized use is not. Relying on the shared social sense when a task genuinely requires coordination (a wedding, a negotiation, a group ritual) is a rational, low-cost use of $S_{ij}$. Relying on it as a default operating principle for private life (identity, personal beliefs, relationships that don't require group consensus) generalizes a tool past its useful domain — the modeling analogue of self-determination theory's distinction between autonomous and externally-controlled motivation (Deci & Ryan, 1985/2000), where chronic reliance on external validation is associated with worse well-being outcomes than autonomously held values.
- Assumption 5 — Harm risk scales with dependency × instability, not dependency alone. A person who is highly dependent on social consensus but whose reference group is stable and consistent may do fine. Risk rises specifically when dependency is high and the social rule-sets being relied on vary or conflict across contexts (family vs. peer group vs. online community) — because the person is trying to satisfy a moving, sometimes contradictory target with their core self-worth on the line.
- Assumption 6 — Social events draw on general holistic capacity, not narrow analytical capacity. Live social performance (reading a room, timing a joke, sensing a shift in mood, responding to nonverbal cues in real time) is resource-intensive in a different way than solving a defined problem. It requires broad, parallel, "whole-picture" processing under tight time constraints — closer to what dual-process theory calls fast/intuitive (System 1) processing than slow/deliberate (System 2) reasoning.
- Assumption 7 — Analytical processing and social/emotional-ego processing compete for the same bounded resource, and tend to suppress each other. This isn't just a metaphor: neuroimaging work by Jack and colleagues (2013) found that the brain's analytical ("task-positive") network and its social/empathic (default-mode-linked) network are reciprocally suppressive — engaging one measurably dampens activity in the other. Separately, Baron-Cohen's empathizing–systemizing theory (2002) frames empathic and systemizing cognition as two distinct processing styles that trade off against each other rather than combining freely. The practical implication: deliberately analyzing a social situation while it's happening (calculating the "right" response, mentally scripting, over-monitoring your own performance) tends to consume the same capacity that live social fluency needs, and typically reads to others as stiffness, delay, or disconnection — a worse outcome than a more intuitive, socially/emotionally attuned response would have produced.
4. Derivation
Step 1 — Represent common sense as a personal rule-set (Assumption 1)
\[R_i = \{r_1, r_2, \dots, r_n\}_i\]
Each $r_k$ is one internalized rule, heuristic, or norm person $i$ commonly applies, built from their own knowledge and experience — not assumed to match anyone else's set.
Step 2 — Overlap defines a shared social sense (Assumption 2)
\[S_{ij} = \frac{|R_i \cap R_j|}{|R_i \cup R_j|}\]
A simple overlap (Jaccard) coefficient: 0 means no shared rules at all, 1 means fully identical rule-sets. Extending to a group of $N$ people, a social sense score for a group is the average pairwise overlap:
\[S_{\text{group}} = \frac{2}{N(N-1)} \sum_{i<j} S_{ij}\]
This is the portion of common sense that is shared, not the portion that is purely private.
Step 3 — Social value dependency (Assumption 3)
\[D_i \in [0,1]\]
$Di \to 1$: self-worth and decisions are almost entirely anchored to how well person $i$'s behavior matches $S{ij}$ (the group's social sense). $D_i \to 0$: self-worth and decisions are anchored to private, self-generated values regardless of group overlap. This directly parallels measured contingent self-worth subscales (e.g., "approval from others," "appearance," in Crocker & Wolfe's contingencies-of-self-worth framework).
Step 4 — Function-boundedness (Assumption 4)
Define a binary/continuous indicator $F_i(t) \in [0,1]$: how much a specific, current task actually requires social consensus (e.g., $F \approx 1$ for a wedding negotiation or group coordination task, $F \approx 0$ for a private belief, hobby, or personal relationship decision).
Effective interference cost — the toll dependency takes on private life — is what's left over when dependency exceeds what the task requires:
\[I_i(t) = D_i \cdot \bigl(1 - F_i(t)\bigr)\]
High dependency during a genuinely social-function task ($F\approx 1$) contributes little interference — the tool is being used where it belongs. High dependency during a private, non-social-function moment ($F\approx 0$) contributes close to the full interference cost.
Step 5 — Harm/injury risk (Assumption 5)
\[H_i(t) \approx D_i \cdot V(t) \cdot \bigl(1 - F_i(t)\bigr)\]
Where $V(t)$ is the instability/conflict of the social rule-sets person $i$ is drawing on at time $t$ (family norms vs. peer norms vs. online-community norms actively contradicting each other). Risk is highest when dependency is high, reference norms are unstable or conflicting, and the context didn't actually require consensus in the first place.
Step 6 — General capacity demand during a live social event (Assumption 6)
\[C_{soc}(t) = C_{base} - \gamma_{Fa}A_{Fa}(t) + \gamma_{active}A_{active}(t)\]
Where $C{base}$ is baseline available capacity, fatigue reduces it as in the source model, and $A{active}(t)$ represents active, embodied engagement (attention, presence, energy actually directed at the interaction) — social performance is not passive; it requires the person to be drawing on capacity in real time, not merely present.
Let $P_i(t) \in [0,1]$ represent how much of person $i$'s real-time output is social/emotional-ego processing (1) vs. analytical processing (0) during a live social moment. Because the two modes reciprocally suppress each other (Assumption 7), define predicted social performance quality:
\[Q_i(t) \approx F_i(t) \cdot P_i(t) \cdot \left(1 - \frac{\text{analytical load}_i(t)}{C_{soc}(t)}\right)\]
When a moment genuinely requires social consensus/coordination ($F \approx 1$) and the person is running in social/emotional-ego mode ($P$ high) with low competing analytical load, performance quality is high. When the same person switches into analytical mode mid-interaction (calculating what to say, over-monitoring, mentally scripting), $P_i(t)$ drops, analytical load rises, and $Q_i(t)$ falls — predicting the common, observable pattern of someone becoming visibly stiffer, slower, or more disconnected the harder they consciously "think through" a social moment.
5. Worked toy example (synthetic numbers, illustration only)
Two people, same dependency level $D = 0.8$ (both heavily anchor self-worth to social approval), both in the same live social event ($F = 0.9$):
Person A stays in social/emotional-ego processing mode during the event: $P_A = 0.85$, low competing analytical load.
$Q_A \approx 0.9 \times 0.85 \times 0.9 = 0.69$ (high performance quality) — and because $F$ is high here, interference/harm stays low: $I_A = 0.8 \times (1-0.9) = 0.08$.
Person B, same dependency and same event, defaults to analytical processing under social pressure — consciously calculating responses, monitoring self-performance: $P_B = 0.25$, high competing analytical load.
$Q_B \approx 0.9 \times 0.25 \times 0.4 = 0.09$ (low performance quality) — even though $I_B$ is the same low value as Person A's, since $F$ is still high, the experience of the event is predicted to feel effortful, awkward, or disconnected despite similar underlying dependency.
Same dependency score, same social-function context; very different predicted performance outcome, because of which processing mode is being run. This is the model's way of formalizing the claim that analytical processing, useful as it is for solving problems, tends to work against someone in the middle of a live social event — social/emotional-ego processing is the better-matched tool for that specific job.
6. What the terms would mean, if this held up
- High $S_{ij}$ between two people → they largely share the same social sense — decisions, jokes, expectations land the same way for both. Low $S_{ij}$ → frequent misunderstanding, not because either person is wrong, but because their private rule-sets barely overlap.
- High $D_i$ used only within high-$F$ moments → someone very socially attuned specifically when it matters, and privately autonomous otherwise — arguably a healthy, situational use of social sensitivity.
- High $D_i$ generalized across low-$F$ private life → someone whose private identity, beliefs, or relationship choices are being run through an external approval filter that was never built for that job — predicted to correlate with chronic stress and identity strain, consistent with findings that approval-contingent self-worth is associated with poorer psychological well-being (Crocker & Wolfe, 2001) and that externally-controlled (vs. autonomous) motivation predicts worse long-term outcomes (Deci & Ryan).
- High $V(t)$ → the person is trying to satisfy multiple, actively conflicting social rule-sets at once (family vs. peer group vs. online norms) — structurally similar to role-conflict and, in a more severe and specific form, the chronic strain described in minority stress theory (Meyer, 2003).
- Low $P_i(t)$ during a social event (analytical mode dominating) → predicted to show up as social awkwardness, delayed responses, or being read as "cold" or "distant" — not because the person lacks social understanding, but because the mode they're running competes with, rather than supports, real-time social output. Consistent with the reciprocal-suppression finding between analytic and social-cognitive brain networks (Jack et al., 2013).
7. Limitations
- The overlap coefficient ($S_{ij}$) is a real, computable quantity in principle — but only if you can actually enumerate someone's "rule-set," which you can't. Real common sense isn't a clean, listable set; this is a modeling convenience, not something you could compute for a real person.
- $D_i$, $V(t)$, and $P_i(t)$ are presented as clean scalars; real dependency, norm-instability, and processing-mode mix are messy, contextual, and change over time, sometimes within the same conversation.
- $F_i(t)$ (how much a task "requires" consensus) is often itself contested — people frequently disagree about whether a given moment is a private matter or a legitimately social one.
- The capacity/processing-mode layer (Section 6, Assumption 7) is a plausible extension grounded in real findings (Jack et al., 2013; Baron-Cohen, 2002), but the specific formula for $Q_i(t)$ is illustrative, not fitted to any data. The reciprocal-suppression research shows the two networks trade off; it does not license a specific numeric weighting of how much any one person's performance degrades.
- This model predicts risk and performance correlationally, not diagnostically. It should never be used to assess or label a specific real person's mental state, relationship, social skill, or worth. If this framework resonates with your own experience, that's worth exploring with a therapist or trusted person, not with a formula.
- No data has been collected against this model. As with earlier documents in this series, the honest next step, if you wanted to test any of it, would be to pick one narrow, measurable piece (e.g., does self-reported over-analysis during social interactions predict lower self- or observer-rated social performance, using existing validated scales) rather than trying to validate the whole framework at once.
This is a structured way to think about two real and related distinctions — situational use of a shared social sense vs. generalized dependency on it, and analytical vs. social/emotional-ego processing during live social performance — built on genuinely established research (contingent self-worth, self-determination theory, minority stress theory, empathizing-systemizing theory, task-positive/default-mode network suppression), with a formal layer (rule-set overlap, function-boundedness, capacity/processing-mode mix) that has not itself been tested.
