{"id":8397,"date":"2026-09-18T17:08:16","date_gmt":"2026-09-18T17:08:16","guid":{"rendered":"https:\/\/rainbowcreciendo.com\/rainbowsantiago\/?p=8397"},"modified":"2026-10-17T08:40:51","modified_gmt":"2026-10-17T08:40:51","slug":"news-news","status":"publish","type":"post","link":"https:\/\/rainbowcreciendo.com\/rainbowsantiago\/2026\/09\/18\/news-news\/","title":{"rendered":"Press & Media | People, Projects & Resources"},"content":{"rendered":"
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Science journalism today is defined by the way people, news \u2014 news<\/a>, projects and resources are integrated to convert complex research into credible public information. In my portfolio, every task begins with a detailed brief, a group of named sources and a documented trail of data, because audiences in the United Kingdom require both precision and transparency. The subsequent sections describe how I select stories, manage collaborations, employ specialist tools, handle ethical questions and keep records that stand up to editorial scrutiny. Audiences will locate specific details on processes, typical costs and the everyday choices that shape each published article.<\/p>\n

Archiving, Credit and Extended Access<\/h2>\n

Posted articles are retrieved as PDF\/A files within 48 hours and archived in a local archive that is backed up to an off-site encrypted drive. Each file is labelled with the ISO date, outlet and slug, allowing quick location when a reader asks for a citation years later. I also place supplementary material such as interview transcripts or analysis scripts in the Zenodo community \u201cScience Journalism UK\u201d, which issues a DOI and guarantees availability for at least twenty years. When a story uses a dataset that cannot be shared for privacy reasons, I record a metadata record that describes the variables and points to the custodian\u2019s access procedure.<\/p>\n

Credit Language for Secondary Sources<\/h4>\n

Secondary sources such as systematic reviews or government statistical releases are framed with a short clause that specifies the producing organisation and the publication date. For example, \u201cOffice for National Statistics data released on 14 March 2024 show\u2026\u201d This format permits readers to judge recency without looking through footnotes and reduces the risk of attributing a finding to an individual researcher when the work was in fact collaborative.<\/p>\n

Ethical Decision-Making in Daily Practice<\/h2>\n

Ethical questions surface most often around patient stories, commercial sponsorship and the use of unpublished images. For patient narratives I acquire written consent that details the level of identification allowed, and I keep the form separately from the interview transcript. When a company presents early access to a device or database, I request a written statement that no editorial control is included; the statement is stored with the project notes and summarized in the published article if the material influences the central claim. Photographs captured at laboratories are authorized with the press department, and any image that displays an individual\u2019s face is paired by a model-release form even if the person is a researcher rather than a patient.<\/p>\n

Handling Corrections and Clarifications<\/h3>\n

Errors are recorded in a public corrections page on my platform, with the date of the original post, the incorrect statement and the corrected text. If the mistake changes a numerical value by more than 5 percent or alters the direction of a finding, I also notify the publisher\u2019s corrections office and seek that the change be recorded in the online version. This approach has contributed in three published clarifications over four annually, each resolved within ten days of the original publication date.<\/p>\n

Picking Projects That Cater to a UK Readership<\/h2>\n

Project selection starts with an assessment of relevance to readers who track policy decisions taken in Westminster and research programmes funded by UK Research and Innovation. I manage a rolling list of fifteen topic areas, covering antimicrobial resistance surveillance by the UK Health Security Agency to offshore wind deployment targets set by the Department for Energy Security and Net Zero. Each candidate story is scored for timeliness, availability of primary data and potential to influence daily life, such as changes in energy bills or medicine supply. Stories that score above an internal threshold move to a one-page treatment detailing the central claim, the evidence required and the expert voices needed to validate it. This scoring sheet follows the assignment from pitch to publication, providing editors a transparent audit trail.<\/p>\n

Creating and Maintaining Source Networks<\/h2>\n

Dependable reporting hinges on a documented network of scientists, clinicians, statisticians and press officers who reply within specified time frames. I hold a contact file that notes each person\u2019s institutional affiliation, publication record and favored channel, whether that is an institutional email or a confirmed Signal number. Before any interview I send a one-paragraph description of the angle, the planned publication and the deadline, which reduces back-and-forth and demonstrates respect for the source\u2019s schedule. After publication I include a short note on how the interview was used, allowing future queries to be precise rather than generic. The file is examined every quarter so that retired researchers are substituted and new group leaders at institutes such as the Francis Crick Institute or the UK Atomic Energy Authority are incorporated while their work is still in preprint.<\/p>\n

Verifying Credentials and Avoiding Conflicts<\/h3>\n

Each new contact is verified against the institutional website and recent peer-reviewed papers found in PubMed or Web of Science. If a researcher has secured funding from a company whose product features in the story, that fact is recorded in the same file and disclosed in the article. I also log when a source has previously counseled government committees, because such experience can offer context but must not be framed as independent commentary. This running ledger stops the common error of quoting the same small circle of voices and guarantees that readers get a balanced range of perspectives.<\/p>\n

Navigating Open Access and Data-Sharing Policies<\/h2>\n

After the publication of the UK government\u2019s 2021 open-access mandate, most publicly funded research papers need to be available under a Creative Commons licence within twelve months. I manage a bookmark folder of institutional repositories and the Europe PubMed Central feed, which together highlight approximately 70 percent of papers cited in my stories before they appear in print. When a paper remains behind a paywall, I use the author\u2019s accepted manuscript, clearly labelled as such, and link to the version of record once it is released. For clinical trial data, I verify the registry record on ISRCTN or ClinicalTrials.gov to confirm primary outcome measures before quoting efficacy percentages, because press releases sometimes emphasise secondary endpoints that were not statistically powered.<\/p>\n

Financial Implications and Time Implications<\/h3>\n

Article processing charges for open-access journals typically vary from \u00a31 500 to \u00a34 500, figures that appear on the journal website before submission. When a paper is only available through a read-and-publish agreement negotiated by Jisc, I mention the licence type in the story\u2019s reference list so readers know they can access the full text without payment. These administrative details rarely appear in the final article, yet they influence whether a claim can be linked directly to primary evidence or must be qualified with the phrase \u201caccording to a pre-print server\u201d.<\/p>\n

Essential Tools for Data Processing and Fact-Checking<\/h2>\n

Each dataset that enters a story is stored into a local repository with file-naming conventions that en.wikipedia.org<\/a> feature the source URL, retrieval date and checksum. I utilize R for initial cleaning when the file exceeds 10 000 rows, and Python\u2019s pandas library when joins across multiple tables are required. A separate plain-text log tracks each transformation step so that an editor or an interested reader can duplicate the figures. For statistical claims I consult the original paper\u2019s supplementary information and, where possible, the analysis code deposited in repositories such as Zenodo. When numbers show up in press releases without underlying data, I request the raw spreadsheet through the institution\u2019s freedom-of-information route and mention the reference number in the story\u2019s endnotes.<\/p>\n

Change Management and Editorial Handover<\/h3>\n

Manuscripts are drafted in plain Markdown inside a private Git repository. Each commit message holds the working headline, the word-count target and the initials of any colleague who has checked a section. Branches are labeled by story slug and are closed after publication, preserving a complete record of changes requested by editors at outlets such as New Scientist or BBC Science. This system avoids accidental overwrites during late-stage edits and permits rapid retrieval of an earlier paragraph if a legal query arises months later.<\/p>\n

FAQ<\/h2>\n

How do you choose which scientific papers deserve coverage for a UK audience?<\/h3>\n

I evaluate each paper on applicability to current UK policy, accessibility of primary data and potential impact on readers\u2019 daily lives. Only papers that meet a minimum score progress to a one-page treatment that outlines required evidence and expert voices. The scoring sheet remains with the assignment from pitch to publication.<\/p>\n

What actions do you take to validate a new source\u2019s credentials?<\/h3>\n

Each contact is checked against their institutional page and recent publications in PubMed or Web of Science. Any industry funding or advisory roles are recorded in a private file and revealed in the article if relevant. The file is examined quarterly to keep details current.<\/p>\n

What software do you use for data cleaning and version control?<\/h3>\n

Large datasets are cleaned in R or Python\u2019s pandas library, with every transformation recorded in a plain-text log. Manuscripts are drafted in Markdown inside a private Git repository so that editors can view the complete change history and earlier versions can be recovered if needed.<\/p>\n

How do you manage corrections after publication?<\/h3>\n

Errors are registered on a public corrections page with the original wording and the correction. If the change exceeds five percent or alters a finding\u2019s direction, the publisher\u2019s corrections desk is also alerted. Most clarifications are resolved within ten days.<\/p>\n

What happens to interview transcripts and datasets after a story is published?<\/h3>\n

Articles are preserved as PDF\/A files and backed up off-site. proceed here<\/a> Supplementary material such as transcripts or analysis scripts is stored in Zenodo with a DOI. Datasets that cannot be released for privacy reasons obtain a metadata record referring to the custodian\u2019s access procedure.<\/p>\n

Do you ask payment readers to access your published articles?<\/h3>\n

No. All articles are featured in outlets that offer open access or stand behind a publisher paywall that libraries can cover through Jisc agreements. I do not maintain a separate subscription site or place articles behind an additional paywall.<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

Science journalism today is defined by the way people, news \u2014 news, projects and resources are integrated to convert complex research into credible public information. 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