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Record W4386812791 · doi:10.56645/jmde.v19i45.701

Excessive Evaluation Anxiety (XEA): The Last Two Decades

2023· article· en· W4386812791 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of MultiDisciplinary Evaluation · 2023
Typearticle
Languageen
FieldHealth Professions
TopicProblem Solving Skills Development
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsStakeholderScopusAnxietyPsychologyThematic analysisIntervention (counseling)Inclusion (mineral)Resistance (ecology)Applied psychologyPublic relationsPolitical scienceSocial psychologySociologyMEDLINESocial scienceQualitative research

Abstract

fetched live from OpenAlex

Background: Excessive evaluation anxiety (XEA) refers to disproportionate or increased evaluation anxiety among those affected by evaluation (e.g., stakeholders) characterized by the sole presence of negative consequences. It can compromise evaluator-stakeholder relationships, presenting as a barrier for program evaluation. Moreover, XEA can both cause and be caused by resistance to evaluation, which is an interrelated topic that shares many common causes, characteristics, and mitigation strategies. The participatory and interactive nature of modern evaluation approaches can exacerbate the presence of XEA. However, researchers have not explored the current state of literature on XEA. Purpose: To explore the current state of the literature on XEA over the past 20 years. Setting: Not applicable. Intervention: Not applicable. Research Design: Literature review. Data Collection and Analysis: We conducted a literature search of Academic Search Complete, Web of Science, and Scopus. We complemented the database search by a journal search of the American Journal of Evaluation, Evaluation, and the Canadian Journal of Program Evaluation. We then conducted a thematic analysis of the articles that met the inclusion criteria. Findings: Upon review of the articles, we identified four main themes in the literature related to XEA. Specifically, XEA: leads to poor evaluator-stakeholder relationships; is influenced by cultural factors; can be mitigated through the development of interpersonal skills; and can be mitigated through a systematic and evidence-based approach to evaluation.

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.

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)0.025
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.319
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0250.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.119
GPT teacher head0.497
Teacher spread0.377 · 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