Quality & trust

Research Integrity

The principles that govern how ENGRexpert works with researchers and organisations.

  • Core principles10
  • Accreditation claimsNone
  • Journal acceptanceNever guaranteed
  • Full policyPublished
Accreditation. ENGRexpert does not claim formal accreditation, certification or regulatory approval. Statements of that kind will be added only when verifiable evidence is supplied. Read the full Research Integrity Policy.

Principles

Ten principles we work by

Transparent methodology

Methods, assumptions and limitations are documented so work can be checked and repeated.

Research integrity

No fabrication, falsification or plagiarism. Work is based on genuine data and sources.

Confidentiality

Confidentiality terms can be agreed in writing; share the minimum needed and avoid sensitive uploads through the public form.

Reproducibility where applicable

Parameters, versions and data handling are recorded so results can be reproduced.

Clear project scope

Deliverables, assumptions and acceptance criteria are agreed before work starts.

Technical review

Results and numbers are checked for consistency before delivery.

Appropriate authorship

Authorship and contribution decisions stay with you and your institution, following journal and institutional policy.

Responsible AI use

AI tools may assist drafting or analysis, but outputs are verified against sources, and AI use is disclosed where policy requires.

No fabricated data or references

Every citation must be a real, verifiable source; gaps are flagged, never filled with invented material.

No guaranteed journal acceptance

Editors and reviewers decide. We support quality and fit, not outcomes.

Principles

Principles in detail

Why research integrity is central to this service

A research support service can easily slide into practices that damage trust: inflating claims, hiding limitations, producing text that misrepresents authorship or implying that results are guaranteed. We treat integrity as a design constraint for our service. This page explains the principles we follow, the requests we decline and the responsibilities that remain with clients. It complements the research integrity policy page, which sets out the commitments in a more formal structure.

Honesty about data and results

We do not fabricate, falsify or selectively omit data. We do not generate invented results to fit a hypothesis, and we do not adjust analyses to reach a desired conclusion. If an analysis shows a result that conflicts with the client's expectation, we report it. If data are insufficient, we say so and describe what additional data would be needed.

Where we perform analysis, we document the steps in scripts or notes so that the client can reproduce and verify them. Good documentation also protects the client if questions arise later.

Authorship, acknowledgement and ghost-writing

Authorship criteria used by many journals require substantial contribution to conception, design, data acquisition or analysis, drafting or critical revision, final approval and accountability for the work. Support services usually do not meet these criteria for the client's research and should be acknowledged where journal policy requires or permits it, rather than listed as authors, unless they genuinely meet the criteria.

We decline to produce complete manuscripts for clients to submit as their own work when the client did not carry out or understand the research. We support authors in writing and improving their own papers, and we ask clients to confirm that they have read and approve the final version.

References and citations

Citations must be real, relevant and accurately represented. We do not invent references or cite sources we have not checked. Generative tools can produce plausible but false citations; any reference suggested by such a tool must be verified against the source. We ask clients to check all references in the final manuscript.

We also discourage excessive self-citation or citation manipulation intended to inflate metrics.

Image, figure and data integrity

Figures must faithfully represent data. Permissible adjustments such as brightness changes must be applied to the whole image and disclosed where journal policy requires. Splicing, cloning or selective editing that alters the meaning is not acceptable. Plots should show the full range of the data where this matters and should not hide variability.

We re-draw figures from underlying data and keep the data files and scripts.

Plagiarism, text reuse and similarity

We do not copy text from other sources without attribution. Reusing one's own previously published text also needs care and, in many cases, citation or permission. Similarity checks are tools to detect problems, not proof of originality. Paraphrasing a source closely without citation is still plagiarism.

We help authors cite properly and restructure text, and we advise on journals' policies on text recycling.

Generative tools and disclosure

Journals differ in their policies on generative tools, but common themes are that tools cannot be authors, that use must be disclosed and that authors are responsible for the content. We do not use generative tools to invent data or references. Where tools assist with language or drafting, the output must be reviewed by a person.

Clients should follow the policy of the target journal and their institution.

Conflicts of interest and independence

We ask clients to disclose conflicts of interest in the manuscript according to journal policy. We do not review work for which we would be a conflicted peer reviewer, and we do not accept requests to produce positive reviews for a client's paper or to manipulate peer review.

We avoid arrangements that would compromise independence, such as writing both a paper and an unaffiliated endorsement of it.

Boundaries and concerns

Data, boundaries and reporting concerns

Confidentiality and responsible data handling

Client materials are treated as confidential and used only for the agreed purpose. Sensitive personal data should not be shared with us unless necessary, and then only through arrangements agreed in advance. Clients remain responsible for ethical approvals, consent and compliance with data-protection laws.

We delete or return files at the end of the engagement according to the agreement.

What we will decline

We decline requests to fabricate or alter data, invent references, write fake reviews, manipulate peer review, submit under false identities, circumvent plagiarism checks or guarantee publication. We also decline work in areas outside our competence or where there is a risk of harm. If a request is borderline, we will explain our concern and offer an acceptable alternative.

These boundaries protect clients as well as the scholarly record.

Reporting concerns

If you believe that something on this website or in our conduct breaches these principles, please contact us. We will review the concern and respond. Concerns about a published paper should be directed to the relevant journal or institution, which have the authority to investigate.

Responsibility for claims in published work

Authors are accountable for the claims in their papers, including claims about novelty, significance and generality. A support service can help to check these claims against evidence, but it cannot take over the responsibility. Reviewers, editors and readers will address questions to the authors.

Preparing for that accountability, by keeping data, scripts and notes organised, is part of good practice and part of what we help clients do.

Integrity in teaching and supervision contexts

Students and supervisors sometimes use support services in ways that blur responsibility. A student who has not performed the analysis should not present it as their own, and a supervisor should not delegate away responsibility for the content of a thesis chapter. Support should leave the student better able to understand and defend the work.

We encourage clients to inform supervisors about the kind of support they use and to follow institutional rules on editing assistance and the use of third-party services in theses.

In practice

Integrity in practice

Practical checklist for authors using support services

Before engaging any editing or research-support service, authors can ask: Will I remain the author who understands and can defend every claim? Will the service refuse to fabricate or alter data? Will references be real and checkable? Will the service respect confidentiality and tell me how my files are handled? Does it avoid guarantees of publication? Does it disclose limits of its competence? Will it put the agreement in writing?

We are happy to answer each of these in writing and invite clients to use the checklist with any provider.

Worked examples of requests we handle

Acceptable: an author asks for help restructuring a discussion section so that limitations are clear. Acceptable: an author asks for a review of the statistical analysis and wants to know whether the tests are appropriate. Acceptable: a team asks for help drafting a response to reviewers that addresses each comment with evidence. Not acceptable: a request to add references that were not read to make a paper look better supported. Not acceptable: a request to generate data to match a model. Not acceptable: a request to rewrite a published paper to evade similarity checks.

These examples are illustrative of how we draw the line. Borderline cases are discussed openly before work starts.

Resources on publication ethics

Recognised organisations publish guidance on authorship, peer review, data sharing, conflicts of interest and handling of misconduct allegations. Authors should consult the policies of their target journal, publisher, institution and funder, which may differ. Training in research integrity is offered by many universities and research councils.

We encourage students and early-career researchers to use these resources and to discuss concerns with their supervisors and research integrity officers.

Questions clients often ask about integrity

Can you guarantee that a reviewer will not find problems? No; we can reduce avoidable problems but not remove all risk. Can you remove similarity-check flags? We can help you cite and restructure text legitimately, but we will not disguise copied text. Can you add citations to strengthen the paper? Only to sources that are relevant and that you have read or that we verify together. Can you make my results look better? No; we can help present them clearly.

Will you tell the journal that you helped me? You decide what to disclose according to journal rules; we will not misrepresent our involvement.

Discuss your project

Share your objectives, data situation and target outcome. We will assess the scope and suggest sensible next steps.