joc-open-science-and-transparency

Open Science & Transparency (joc-open-science-and-transparency)

JoC requires a Data Availability Statement on every article and offers Open Science Badges for

open data, open materials, and preregistration. Transparency is not an afterthought — build the

statement and supporting materials as you write so submission and any badge claim go smoothly.

When to trigger

• Drafting the Data Availability Statement (a submission requirement)
• Deciding whether to pursue Open Science Badges (open data / open materials / preregistration)
• Preparing a preregistration for a prospective design (note it in the cover letter)
• Data cannot be fully shared (privacy, ethics, platform/legal restrictions) and you need the path forward

What JoC expects (verify current wording on the policy page)

1. Data Availability Statement (required). State where the data are (repository + identifier),

under what conditions they can be accessed, and — if they cannot be shared — why, with

instructions for how others might obtain them.

1. Open Science Badges (optional, earned).

• Open Data — data and a codebook deposited in a trusted repository with a persistent identifier.
• Open Materials — stimuli, instruments, code, and protocols deposited so the study can be reproduced.
• Preregistration — a time-stamped, registered design/analysis plan; note it in the cover letter.

1. Quantitative / computational materials. Data, code, codebook, and documentation sufficient to

regenerate every reported result; master script + README + pinned versions + seeds; for automated

text measures, include the human-validation materials.

1. Qualitative materials. Share the materials that support the claims (e.g., coding schemes,

evidence tables, de-identified excerpts) with access controls where needed (QDR for controlled access).

When data cannot be shared (restricted-data path)

• Explain why in the Data Availability Statement (ethical/privacy concerns, platform terms of

service, or legal restrictions by the provider).

• Provide instructions on how others can obtain the data (access process, application, provider contact).
• Where possible, provide synthetic or de-identified data so the code can be run.

Build-as-you-go checklist

• [ ] Data Availability Statement drafted (repository, identifier, access conditions, or exemption)
• [ ] One master script regenerates every table and figure from raw/constructed data
• [ ] README documents data provenance, construction, and how to reproduce each exhibit
• [ ] Seeds set and reported for every stochastic step; software/package versions pinned
• [ ] Open Science Badge materials staged (open data / open materials / preregistration) where claimed
• [ ] Content analysis: codebook + intercoder-reliability report included
• [ ] Materials anonymized (no author-identifying paths/links) for double-anonymous review

Transparency expectations by communication method (decision table)

Because JoC spans communication research broadly, "transparency" differs across traditions. Match the

deposit to the method rather than forcing one template:

| Method | What a JoC referee wants deposited | Badge most relevant |

|--------|------------------------------------|---------------------|

| Survey / message experiment | data + codebook + stimuli + analysis script | open data + materials + preregistration |

| Content analysis | codebook + coder instructions + reliability subsample + texts | open materials (+ open data) |

| Computational / text-as-data | corpus or query, model/version, seeds, human-validation set | open materials + open data |

| Qualitative / critical | coding scheme + evidence tables + de-identified excerpts | open materials where ethics allow |

For computational measures, the human-validation set is itself the evidence that the automated

label means what the paper claims — depositing the classifier without it leaves the construct

unverified. Confirm badge mechanics against the journal's current guidance.

Worked micro-example: a DAS for a copyrighted-news corpus (illustrative)

A computational content analysis of 40,000 news articles (illustrative) on climate coverage hits

a familiar wall: the texts are copyrighted and the feed bars redistribution. The transparency path:

(1) deposit the codebook, article IDs/URLs, query parameters, and analysis code so a same-license

reader reproduces the pipeline; (2) deposit the human-validation sample, shareable derived data;

(3) write a DAS naming the restriction, provider, and access route, and offering **de-identified

derived features** (frame proportions per article) so modeling re-runs without raw text — earning

open-materials credit and an honest, hedged DAS.

Anti-patterns

• Submitting without a Data Availability Statement (it is required)
• Claiming a badge whose materials are not actually deposited or do not reproduce the results
• A personal URL instead of a trusted repository with a persistent identifier
• Claiming data are restricted without giving an access path or synthetic substitute
• De-anonymizing the manuscript via an open-materials link during review

Output format

【Data Availability Statement】drafted? repository + identifier or exemption? [Y/N]
【Reproduces tables/figures?】master script verified locally? [Y/N]
【Badges sought】open data / open materials / preregistration (materials staged?)
【Documentation】README + provenance + seeds + pinned versions? [Y/N]
【Restricted data?】exemption note + access path + synthetic data?
【Qualitative transparency】coding scheme / evidence documented? [Y/N/NA]
【Next】joc-review-process

Supplementary resources

• [../../resources/external_tools.md](../../resources/external_tools.md) — reproducibility tooling and qualitative-transparency options (OSF, QDR)
• [../../resources/official-source-map.md](../../resources/official-source-map.md) — Data Availability Statement requirement + Open Science Badges