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Record W4413452824 · doi:10.1016/j.copsyc.2025.102153

The OTTER framework: Willful ignorance as the greatest barrier to allyship at work and five steps to overcome it

2025· review· en· W4413452824 on OpenAlexfundno aff
Hsuan‐Che Huang

Bibliographic record

VenueCurrent Opinion in Psychology · 2025
Typereview
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsnot available
FundersUniversity of British Columbia
KeywordsIgnorancePsychologyWork (physics)ChemistryOtterEpistemologyEcologyMechanical engineeringEngineering

Abstract

fetched live from OpenAlex

Despite growing equity, diversity, and inclusion (EDI) efforts in organizations, many socially advantaged individuals remain inactive as potential allies. To understand why, the present article introduces willful ignorance-the conscious avoidance of knowledge about inequality-as a core psychological barrier to allyship. Reviewing and synthesizing insights from existing research, we show how two forms of willful ignorance manifest at work (passively overlook among the "left" and actively turn away among the "right" on the ideological spectrum) and propose the OTTER framework to address them: Observe, Think, Talk, Examine, and Reorient. By illustrating how each intervention step disrupts willful ignorance among advantaged group members, we offer theoretical and practical guidance for advancing workplace EDI. This work further opens a pathway for future research on willful ignorance in allyship contexts.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.760
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.121
GPT teacher head0.508
Teacher spread0.387 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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