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Record W2932220783 · doi:10.22215/etd/2016-11554

The Construct Validity of Active Procrastination: Is it Procrastination or Purposeful Delay?

2016· dissertation· en· W2932220783 on OpenAlexaff
Shamarukh Chowdhury

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPsychology
TopicPerfectionism, Procrastination, Anxiety Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsProcrastinationPsychologyConstruct (python library)ConscientiousnessNomological networkSocial psychologyConstruct validityScale (ratio)Developmental psychologyPersonalityBig Five personality traitsPsychometricsExtraversion and introversionComputer science

Abstract

fetched live from OpenAlex

Research over the past decades has shown that procrastination is an instance of selfregulation failure with deleterious consequences.Surprisingly, Chu and Choi (2005) have coined a construct called active procrastination emphasizing that procrastination can lead to positive outcomes despite the deferral of tasks on purpose until the last minute.The present study examined the construct validity of active procrastination.Using important antecedents (e.g., self-regulation, intention-action gap), correlates (e.g., self-efficacy beliefs, conscientiousness) and related outcomes of procrastination (e.g., stress, depression) as identified in the extant research literature, correlational results revealed that active procrastination has been mislabeled as a type of procrastination that is more appropriately construed as purposeful delay with adaptive qualities.The present study failed to replicate the nomological network of active procrastination demonstrated in previous research.Limitations associated with the active procrastination construct, empirical evidence and the corresponding inferences in developing the Active Procrastination Scale are discussed.iii Acknowledgement First and foremost, I would like to express my gratitude to Dr. Tim Pychyl whose invaluable support and guidance at every step of the way made this Masters project come to fruition.Thank you for your continuous encouragement throughout this adventure.I still remember the day when you told me that you would supervise my Masters project.It was one of the most exciting days of my life.Not only it was a chance for me to pursue a graduate degree but to learn from the best.Because of that great opportunity, I am here today completing my Masters degree.Thank you for seeing the researcher in me and letting me work on this interesting project.I have learned a lot from you in these past two years.Your immense knowledge, countless feedback and advice, and keen eye for details helped me to grow as a researcher and inspired me to complete my degree in a purposeful manner.I will always be grateful for this opportunity, the opportunity to learn from you.I would also like to extend my appreciation to my committee members, Dr. Cheryl Harasymchuk, Dr. Marina Milyavskaya and Dr. George Pollard for their interesting insight and feedback in shaping the final

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.016
metaresearch head score (Gemma)0.066
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.016
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.066
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.010
Scholarly communication0.0040.004
Open science0.0020.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.047
GPT teacher head0.362
Teacher spread0.315 · 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 source (direct Gemma or distilled Codex), 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

Citations8
Published2016
Admission routes1
Has abstractyes

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