Online Turnitin & AI Similarity Explainer & Rebuttal Generator

DATE: September 30, 2026 TO: Dr. Elizabeth Vance, Editor-in-Chief INSTITUTION: Journal of Applied Social Psychology FROM: Sarah Jenkins, MSc, Corresponding Author / PhD Candidate SUBJECT: Formal Rebuttal & Methodological Justification Regarding Turnitin Similarity & AI Detection Report MANUSCRIPT TITLE: "Examining Workplace Psychological Safety in Remote Teams: A Longitudinal Survey" DEAR COMMITTEE / EDITORIAL BOARD, This correspondence provides formal academic documentation and clarification regarding the Turnitin automated report generated for the aforementioned manuscript, which indicated a general similarity index of 11% and an AI writing probability of 32%. I affirm unequivocally that this research was conducted and written with rigorous adherence to academic integrity, institutional guidelines, and international publication ethics (COPE). I respectfully present the following itemized contextual clarifications: 1. SUBSTANTIVE APPRAISAL OF DETECTED MATCHES The flagged AI probability of 32% represents an algorithmic false positive and does not reflect unauthorized artificial intelligence generation. As documented in Turnitin's own official technical literature ('Understanding False Positives in AI Writing Detection') and prominent empirical research (e.g., Liang et al., 2023, Stanford University), AI text classifiers disproportionately flag formal, structured academic prose and formulaic empirical phrasing. The entire research and writing process was executed autonomously by the undersigned author, as substantiated by the forensic timestamp logs and version history appended hereto. 2. PARAMETRIC FILTERING AUDIT - Bibliography Exclusion: Active (Properly Excluded) - Quoted Material Exclusion: Active (Properly Excluded) - Small Match Filtering: Active Additional Context: Turnitin flagged repetitive statistical terminology and formulaic demographic descriptors in the Methods section. 3. DOCUMENTARY EVIDENTIARY RECORD In accordance with international verification standards, the following documentary evidence is submitted herewith to demonstrate genuine human authorship: 1. Word / Google Docs Version History: Total editing time records and timestamped paragraph revisions documenting natural human drafting. 2. Reference PDF Archive (Zotero / Mendeley): Timestamped full-text PDFs of all cited publications corresponding to annotated notes. 3. Initial Outlines & Research Notes: Handwritten notes, early conceptual drafts, and supervisor correspondence logs. 4. IRB / REC Approval & Raw Dataset: Official institutional ethics approval certificates, questionnaires, and raw SPSS/R datasets. CONCLUSION AND FORMAL REQUEST: Pursuant to Turnitin's official technical guidance, automated similarity and AI classification outputs do not constitute definitive proof of academic misconduct; rather, they serve as preliminary screening indicators requiring informed qualitative editorial judgment. In light of the technical filtering anomalies and the forensic evidentiary record provided, I respectfully request that: a) The similarity assessment be re-evaluated with standard bibliographic and quotation exclusions activated; b) The manuscript's substantive originality and ethical compliance be reaffirmed to allow regular progression through review. Respectfully submitted, Sarah Jenkins, MSc Corresponding Author / PhD Candidate Signature: _______________________