Terms and Conditions

Meta-Student Platform — Sports Science Replication Centre
Last updated: March 2026

By registering your intent to participate and/or submitting data to the Meta-Student platform, you agree to the following terms. Please read them carefully. If you do not agree, do not register or submit.

1. Nature of the Project

The Meta-Student platform is a collaborative research initiative coordinated by the Sports Science Replication Centre but is not limited to Sports and Exercise Science. Its purpose is to pool independently collected student datasets to produce a peer-reviewed, living meta-analysis. Data submitted by participants will be aggregated with data from other contributors and analysed statistically to produce pooled effect size estimates and associated outputs.

2. Data Transfer and Storage

By submitting your dataset you consent to:

  • Your data file, summary statistics, ethics approval letter, and methods report being uploaded to and stored on the Meta-Student platform servers.
  • Your submitted data being retained for the duration of the project and for a minimum of 10 years after the publication of any resulting meta-analysis, in accordance with open-science and research-integrity requirements.
  • Authorised platform administrators and the project coordination team being able to view your submission files for the purpose of quality review and analysis.
  • Your anonymised participant-level data (with all personal identifiers removed prior to upload) being shared in an open data repository alongside any resulting publication, in line with open-science best practice.

You are responsible for ensuring the data you submit is anonymous. Meta-Student accepts anonymous data only. Data is anonymous when no one — including you — can identify any participant from it, which means the key linking participant numbers to real people must be destroyed before you submit. Section 3 sets out how to achieve this, and you will be asked to confirm it explicitly at the point of upload. Your supervisor is asked to confirm it independently before your submission proceeds.

3. How to Anonymise Your Data

Meta-Student accepts anonymous data only. This is a condition of submission, not a recommendation. Anonymous is a stronger standard than “de-identified”: data is anonymous only when no one can identify a participant from it, including you.

The distinction that matters is the key — the list, spreadsheet or notebook page linking participant numbers to real people. While that key exists anywhere, the data is pseudonymised, someone can still work back to an individual, and it remains personal data under data-protection law. Once the key is destroyed, nobody can. Destroying it is what makes your submission anonymous.

Before you submit, work through each step:

  1. Remove every direct identifier. No names, student numbers, email addresses, phone numbers, addresses, signatures or photographs anywhere in the file. Replace a date of birth with age in whole years — a full date of birth is itself an identifier.
  2. Use meaningless participant numbers. Number participants 1, 2, 3 and so on. Do not build the code from anything real: not initials, not a birth date, not a jersey number, not the order they appear on a class list. A code that can be decoded is not anonymous.
  3. Destroy the linking key before you submit. This is the step that makes the data anonymous rather than pseudonymous. Delete the file, spreadsheet, notebook page or message that maps participant numbers to real people — from your laptop, your cloud drive, your email sent items, any shared drive, and any backup or printout. If a key survives anywhere, the data is not anonymous and must not be submitted.
  4. Check for indirect identifiers. Someone can be identifiable without being named. Watch for rare combinations that single a person out in a small sample, free-text notes describing an injury or personal circumstance, and exact testing dates that could be matched to a timetable or a training log. Remove or coarsen them.
  5. Clean the file itself, not just the visible cells. Spreadsheets carry more than you can see: hidden columns and sheets, filters, cell comments, tracked changes, and document properties naming the author. Check the filename too — "JMurphy_participants.xlsx" identifies someone before the file is even opened.
  6. Do it before upload, and understand it is final. Keep your key while you still need it for your own project, then destroy it as the last step before submitting here. Once anonymous data is submitted, neither you nor we can find or remove any individual’s record, because nobody can tell which record belongs to whom. Your participants must be told this when they consent.

Timing.Keep your key for as long as your own project genuinely needs it — for repeat testing sessions, for your own write-up, or to meet your institution’s requirements. Destroy it as the final step before you submit here.

This is irreversible, and your participants must know that. Once anonymous data has been submitted, no individual record can be found, corrected or withdrawn, because nobody can tell which record belongs to which person. Your participant information sheet and consent form must say so before anyone agrees to take part. If a participant may later want their data removed, do not submit their data.

You confirm at upload that no identifying information and no participant ID key remain anywhere, and that identification is not possible. Your supervisor confirms the same independently. A submission that cannot honestly carry both confirmations must not be made.

4. Data Sharing Agreement

All contributors are required to sign and upload a Data Sharing Agreement (DSA)at the point of data submission. The DSA is a formal record of the terms under which your dataset is contributed to the Meta-Student project and must be signed by both the student and their supervisor.

A copy of the DSA is automatically attached to your registration confirmation email. It can also be downloaded at any time from the submission page. Submissions without a signed DSA will not be accepted. By signing the DSA you confirm that:

  • You understand and agree to the data storage, sharing, and publication terms set out in this document and in the DSA itself.
  • Your supervisor has reviewed and countersigned the DSA, confirming they are aware of and endorse your participation.
  • The signed document you upload is genuine and unaltered.

5. Use in Publication

By submitting your data you explicitly consent to:

  • Your dataset being included in a pooled meta-analysis that will be submitted for peer-reviewed publication in an academic journal.
  • Summary statistics derived from your data (effect sizes, confidence intervals, sample characteristics) being reported in the resulting publication and any associated pre-registration, conference presentations, or supplementary materials.
  • The project being pre-registered on an open registry (e.g. OSF, AsPredicted) prior to or during data collection, which may include aggregate information about the study design and expected number of contributors.

6. Authorship and Attribution

Full authorship credit is a core commitment of the Meta-Student project and a primary benefit of participation. Every contributor whose submission passes quality review and is included in the final meta-analysis will be listed as a named co-author on the resulting peer-reviewed publication [All studies will be submitted for publication, but we cannot guarantee publication, see box below].

  • Your name and institutional affiliation will appear in the author list of the manuscript exactly as you provide them on the platform.
  • Where a journal requires a condensed author list due to volume of contributors, a collective author name will be used (e.g. “The Meta-Student Collaboration”) with all individual names listed in full in a dedicated Contributors section or supplementary file — ensuring your contribution is formally and permanently on record.
  • You will be contacted by email before the manuscript is submitted for peer review to confirm your author details, review the draft, and provide any final approval.
  • Authorship is contingent on your submission being included in the analysis. Submissions that are excluded following quality review will not receive authorship credit, though contributors will be informed of the reason for exclusion.

This authorship model is what makes the Meta-Student project distinctive. By contributing rigorous, protocol-adherent data you are a genuine co-author of a peer-reviewed meta-analysis — not merely an acknowledged data donor.

No guarantee of publication. While the project team will make every reasonable effort to submit the completed meta-analysis for peer-reviewed publication, no guarantee of acceptance or publication can be made. Acceptance is at the sole discretion of the target journal and its peer reviewers. Participation in the project does not constitute a promise of a published output, and no liability is accepted for outcomes dependent on publication (e.g. academic credit, career progression).

Supervisors. Supervisors who approve student registrations and submissions fulfil a quality-assurance and oversight role. This role alone does not qualify supervisors for authorship credit on any resulting publication. Supervisors who wish to be considered for authorship must make a separate, substantive intellectual contribution to the project (e.g. contributing to the study design, protocol, analysis plan, or manuscript drafting) and thus must meet the ICMJE authorship criteria independently of their supervisory duties.

7. Ethical Responsibility

You confirm that:

  • Ethical approval was obtained from a recognised institutional ethics committee or review board before data collection began.
  • All participants provided written informed consent prior to participating.
  • Data collection was conducted in accordance with the Declaration of Helsinki and your institution's ethical standards.
  • The ethics approval letter you upload at submission is genuine, unaltered, and issued on official institutional headed paper with the relevant authorising signature(s).
  • Submission of falsified, altered, or fabricated ethical documentation may constitute research misconduct and will result in immediate exclusion from the project and referral to your institution.

8. Data Integrity and Accuracy

You confirm that all data submitted is genuine, accurately recorded, and collected in accordance with the project protocol. Any deviations from the protocol must be documented in your methods report. Submission of fabricated or manipulated data constitutes research fraud and will be reported to your institution.

9. Right to Withdraw

You may request withdrawal of your submission prior to the data being included in a published meta-analysis by contacting the project coordinator. Once a manuscript has been accepted for publication, withdrawal may not be possible. Requests should be sent to the project coordinator with your submission ID.

10. Contact

For questions about these terms, data use, or to request withdrawal, contact:
Joe Warne — Sports Science Replication Centre