Third-Party Tracking in Online Public Library Environments in the United States and Canada: A Statistical Analysis
Bibliographic record
Abstract
A Review of:Gardner, G. J. (2021). Aiding and abetting: Third-party tracking and (in)secure connections in public libraries. The Serials Librarian, 81(1), 69–87. https://doi.org/10.1080/0361526X.2021.1943105 Objective – To determine through statistical data collection the frequency of tracking by third parties in online public library environments along with the visibility and ease of discovery of online library policies and disclosures related to third-party tracking in particular and data privacy in general. Design – Online evaluation of public library websites. Setting – English-language public libraries in the United States and Canada. Subjects – 178 public library websites (133 in the United States and 45 in Canada). The libraries included in the study were intentionally selected for their membership in either the Canadian Urban Libraries Council (CULC) or the Urban Libraries Council (ULC) in the Unites States, since these libraries have some of the largest systems membership serving predominantly urban and suburban communities in both countries. The included Canadian libraries serve nearly 41% of the population in that country while the included libraries in the United States are positioned to serve 28% percent of the total population. The author notes that “These percentage figures serve as hypothetical, upper-bound estimates of the population affected by third-party tracking since not every member of these communities actually uses their local public library” (Gardner, 2021, p.72). Methods – In addition to evaluating the public library catalog and website in general with regards to third-party tracking and data privacy, 10 common content sources (databases) available at all of the included libraries were also included in the examination. Two browser add-ons designed to detect third-party tracking, Ghostery and Disconnect, were used in the study due to their popularity and incorporation into previous similar studies. In addition to third-party tracking the author executed word searches on library homepages using Ctrl-F for words commonly used to denote privacy or terms of use statements. No qualitative analysis was performed to determine if information shared regarding third-party tracking was accurate, and subpages were not examined. The data collection period lasted a total of three months beginning in March 2017 and running through May 2017. Main Results – The data gathered between March and May of 2017 clearly indicates a general disregard among most sampled public libraries regarding the protection of patron data gathered by third-party tracking. Of Canadian libraries included in the sample 89% (40) enabled third-party tracking, while libraries in the United States allowed it at a rate of 87% (116). Both Ghostery and Disconnect revealed an almost identical number of incidences of third-party tracking in library catalogs and in the 10 popular public library databases examined in the study. Certain OPACS were associated with higher tracking counts as were certain library databases. Libraries were found to be lax when it came to providing a link on the homepage potentially informing users of the presence of third-party tracking. Of the 156 total libraries with third-party tracking in their online catalogs, 69 (44%) included a homepage link while the rest did not. The author notes that the presence of a link was all that was examined, and not specific language used to disclose the level of third-party tracking or data privacy. In total, 8 of the 10 common content sources allowed third-party tracking. All 10 provided a link to either privacy or terms of service statements on their landing pages. Conclusion – Although patron privacy is an issue addressed in the American Library Association (ALA) Code of Ethics (American Library Association, 2021), the author concludes that “Together with previous research on usage of privacy-enhancing tools in public libraries, these results suggest that public libraries are accessories to third-party tracking on a large scale” (Gardner, 2021, p.69).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.110 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".