MétaCan
Menu
Back to cohort
Record W3161232446 · doi:10.31234/osf.io/spm9a

From ego depletion to self-control fatigue: A review of criticisms along with new perspectives for the investigation and replication of a multicomponent phenomenon

2021· review· en· W3161232446 on OpenAlexaff
Cyril Forestier, Margaux de Chanaleilles, Matthieu P. Boisgontier, Aïna Chalabaëv

Bibliographic record

Venuenot available
Typereview
Languageen
FieldPsychology
TopicMental Health Research Topics
Canadian institutionsBruyèreUniversity of Ottawa
Fundersnot available
KeywordsEgo depletionId, ego and super-egoPsychologyReplication (statistics)PhenomenonSocial psychologyControl (management)Self-controlFalsifiabilityCognitive psychologyEpistemologyComputer scienceMedicineArtificial intelligence

Abstract

fetched live from OpenAlex

The replication crisis in psychology has led to question popular phenomena such as ego depletion, which has been criticized after studies failed to replicate. Here, we describe limitations in the literature that contributed to these failures and suggest how they may be addressed. At the theoretical level, the literature focuses on two out of at least eight identified auxiliary hypotheses. Thus, the majority of the hypotheses related to the three core assumptions of the ego-depletion theory have been overlooked, thereby preventing the rejection of the theory as a whole. At the experimental level, we argue that the low replicability of ego-depletion studies could be explained by the absence of a comprehensive, integrative, and falsifiable definition of self-control, which is central to the concept of ego depletion; by an unclear or absent distinction between ego depletion and mental fatigue, two phenomena that rely on different processes; and by the low validity of the tasks used to induce ego depletion. Finally, we make conceptual and methodological suggestions for a more rigorous investigation of ego depletion, discuss the necessity to take into account its dynamic and multicomponent nature, and suggest using the term self-control fatigue instead.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.892
Threshold uncertainty score0.592

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.172
GPT teacher head0.477
Teacher spread0.305 · 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 designOther design
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

Citations7
Published2021
Admission routes1
Has abstractyes

Explore more

Same topicMental Health Research TopicsFrench-language works237,207