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Record W3185303701 · doi:10.3389/feduc.2021.620827

Measuring Privileged Identity in Educational Environments: Development and Validation of the Privileged Identity Exploration Scale

2021· article· en· W3185303701 on OpenAlexaff
Sherry K. Watt, John A. Mueller, Eugene T. Parker, Rebecca Neel, Kira Pasquesi, Cindy Ann Kilgo, Amanda L. Mollet, Duhita Mahatmya

Bibliographic record

VenueFrontiers in Education · 2021
Typearticle
Languageen
FieldPsychology
TopicCommunication in Education and Healthcare
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIdentity (music)Scale (ratio)PsychologyConfirmatory factor analysisFacilitationSocial psychologyExploratory factor analysisSociologyComputer sciencePsychometricsDevelopmental psychologyStructural equation modelingAestheticsGeography

Abstract

fetched live from OpenAlex

The present study describes the development and validation of an instrument to measure defensive reactions individuals display in difficult dialogues while exploring privileged identities and interacting across difference. The increased focus on difficult dialogues when exploring privileged social identities in educational environments points to a need for the Privileged Identity Exploration Scale (PIE-S). The Privileged Identity Exploration Model (PIE) (Watt, College Student Affairs Journal., 2007, 26, 114–126; Watt et al., Counselor Education and Supervision., 2009, 49, 86–105) identifies eight defensive reactions. Using exploratory and confirmatory factor analysis, we identified and confirmed four constructs of privileged identity exploration that students exhibit when interacting across social differences, the PIE Scale (PIE-S). We provide a brief overview of the development of the PIE-S, as well as future directions for research and applications to training and facilitation in various educational settings.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.542

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.055
GPT teacher head0.347
Teacher spread0.292 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations5
Published2021
Admission routes1
Has abstractyes

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