In the Name of Justice: Affective Polarization and the Futures of Societal Coordination
Bibliographic record
Abstract
Affective polarization is a societal condition that, if left unregulated, can have detrimental effects on our ability to coordinate and make informed decisions, particularly in the face of challenging circumstances. The purpose of this inquiry is to uncover the driving forces behind the emergence and escalation of affective polarization. Using the principles and tools of design thinking, systems thinking, and futures thinking, the current state of the system is investigated in the context of three dimensions: our individual experience (identity), our relational interactions (coordination), and our material observation (knowledge), all of which interact to form an emergent property—decision-making. \n \nThis research reveals that our beliefs are fused to our sense of virtue, which provides a rationale for the hostility that arises when those beliefs are questioned by conflicting perspectives. It also presents evaluation criteria for assessing coordinative capacity, which is used to evaluate the state of the current system. A set of four alternative futures states are then envisioned to consider potential outcomes based on how Canadian society elects to deal with the problem we are currently facing. The four outcomes are based on a multilateral decision to exit the situation, a unilateral decision to adapt to the situation, a unilateral decision to force a situation, or a multilateral decision to collaborate. These scenarios are assessed with the same coordinative capacity evaluation criteria, where all five states (current and futures) are compared. \n \nThe assessment results produce a theoretical framework defined as the Four C’s for Enabling Coordinative Capacity (curiosity, connection, courage, and collaboration), which are a set of proposed core values and corresponding guiding principles intended to underpin any strategic anti-polarization or depolarization initiatives for increasing social coordination and informed decision-making.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.032 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".