Open science movements get captured by technology companies

The open science movement sold itself as liberation from academic gatekeepers. What it delivered was a more sophisticated form of capture—one where technology companies control the entire infrastructure of scientific communication while researchers celebrate their “freedom.”

This isn’t a story about good intentions gone wrong. It’s about how corporate entities systematically co-opt movements that threaten their control by offering seemingly superior alternatives.

The original promise versus delivered reality

Open science advocates promised to break the stranglehold of traditional academic publishers. No more paywalls. No more artificial scarcity. No more gatekeeping by editorial boards with questionable agendas.

The movement succeeded in delegitimizing the old system. Researchers increasingly recognize that paying $3,000 per article to publish in journals owned by corporations like Elsevier represents an absurd transfer of value from publicly-funded research to private profit.

But critique of the old system doesn’t automatically generate better alternatives. It creates a vacuum that gets filled by whoever has the resources to build infrastructure at scale.

Technology companies had those resources.

Platform dependency as the new gatekeeping

ArXiv, ResearchGate, Academia.edu, Google Scholar, Mendeley—the landscape of “open” science now runs on platforms controlled by technology companies or organizations dependent on their funding.

Each platform offers genuine improvements over traditional publishing:

Immediate publication without peer review delays
Global accessibility without subscription barriers
Social networking features that connect researchers
Analytics that track impact and engagement
Integration with research workflows and tools

These benefits are real. They’re also the mechanism of capture.

Researchers who adopt these platforms become dependent on their continued operation, their policies, their algorithms, their business models. What appears as liberation from one form of control becomes submission to another.

The algorithmic curation problem

Traditional academic gatekeeping was flawed but transparent. Editorial boards made decisions based on stated criteria. The process was slow and often biased, but researchers understood how it worked.

Platform-mediated science operates through algorithmic curation. Recommendation systems determine which papers get visibility. Search algorithms decide what counts as relevant. Engagement metrics become proxy measures for scientific value.

This creates a fundamental shift in how scientific knowledge gets filtered and prioritized. Instead of human judgment applied to content, we have automated systems optimizing for platform-specific engagement metrics.

The criteria for scientific value become whatever keeps users active on the platform.

Data extraction and behavioral modification

Technology companies don’t provide free platforms out of altruism. They extract value from user data and behavior in ways that researchers rarely fully comprehend.

Every search query, every paper download, every citation pattern, every collaboration request generates data about research trends, institutional relationships, and individual researcher behavior.

This data gets used to:

Predict future research directions for investment purposes
Identify promising researchers for recruitment
Map intellectual property landscapes for patent applications
Optimize platform features to increase user dependency
Sell analytics services back to institutions and funding agencies

Researchers think they’re using free tools. In reality, they’re providing unpaid labor to generate data products sold to other parties.

The network effects trap

Once a critical mass of researchers adopts a platform, it becomes practically impossible for others to avoid it. If your field conducts discussions on ResearchGate, you must join ResearchGate to participate in your field.

This creates powerful network effects that lock researchers into platform ecosystems. Even researchers who understand the risks of platform dependency often have no realistic alternative.

Individual resistance becomes professionally self-defeating. The collective action required to build alternatives faces coordination problems that favor incumbent platforms with existing user bases.

Institutional complicity

Universities and funding agencies accelerated platform capture by adopting metrics derived from these systems for evaluation purposes.

Download counts from ArXiv, citation metrics from Google Scholar, social media engagement from Twitter—these platform-generated numbers became official measures of research impact.

This created institutional pressure for researchers to optimize their work for platform algorithms rather than scientific rigor. The evaluation system itself becomes dependent on technology company infrastructure.

The standardization of scientific communication

Platform-mediated science tends toward standardization. User interfaces impose particular ways of organizing information. File formats limit how research can be presented. Social features encourage certain types of interaction while discouraging others.

This isn’t neutral infrastructure. It’s opinionated technology that shapes how researchers think about and communicate their work.

Over time, the platform’s organizational logic becomes internalized as the “natural” way to do science. Alternative approaches become literally unthinkable because the tools don’t support them.

Venture capital and the research agenda

Many “open science” platforms operate on venture capital funding with expectations of eventual monetization or acquisition. This creates inherent tensions between researcher interests and investor returns.

Features get optimized for growth metrics rather than scientific utility. Business model pivots can suddenly eliminate functionality that researchers depend on. Acquisition by larger technology companies can fundamentally alter platform priorities.

The promise of “open” science becomes contingent on private investment strategies that researchers have no influence over.

The myth of technological neutrality

Technology companies promote their platforms as neutral infrastructure that simply enables researchers to do what they already wanted to do more efficiently.

This framing obscures how platform design shapes research practices. The available affordances determine what kinds of research questions become feasible, what forms of collaboration are possible, what counts as evidence, and how knowledge gets validated.

There is no neutral technology. Every platform embeds particular assumptions about how scientific work should be organized and evaluated.

Regulatory capture through expertise

Technology companies increasingly position themselves as experts on scientific communication, offering consulting services to universities and funding agencies on “digital transformation” of research.

This creates regulatory capture where the organizations responsible for overseeing scientific institutions receive guidance from the same companies that profit from platform dependency.

Policy recommendations predictably favor solutions that increase reliance on technology company services while framing alternatives as technically infeasible or economically impractical.

The centralization of scientific infrastructure

The open science movement aimed to democratize access to knowledge. Instead, it contributed to centralizing control over scientific infrastructure in the hands of a small number of technology companies.

This centralization creates systemic vulnerabilities. Platform outages can disrupt global research communication. Policy changes can eliminate functionality that entire fields depend on. Business failures can destroy years of accumulated data and social connections.

More fundamentally, it places the future of scientific communication at the mercy of corporate strategies that researchers have no influence over.

What genuine alternatives would require

Building truly independent scientific communication infrastructure would require:

Sustainable funding models not dependent on data extraction
Governance structures controlled by research communities
Technical standards that prevent platform lock-in
Institutional policies that resist metric gaming
Collective commitment to supporting alternative platforms even when they’re less convenient

These requirements highlight why technology company capture was so successful. They offered immediate individual benefits while avoiding the collective action problems that genuine alternatives require.

The value question

The fundamental issue isn’t whether technology company platforms provide useful services to researchers. They obviously do.

The question is whether the long-term costs of platform dependency outweigh the short-term benefits. Whether researchers are trading away control over their professional infrastructure for convenience features.

Whether the “openness” of science should be defined by accessibility to existing knowledge or by autonomy over the systems that produce and distribute that knowledge.

The open science movement succeeded in making research more accessible. But accessibility without autonomy may simply be a more efficient form of control.

The captured movements never recognize their capture. They celebrate their liberation while strengthening the chains that bind them.