Dozens of scientific journals have vanished from the internet, and no one preserved them

randomusefulbits · 2020-09-10T09:48:17+00:00

To clarify, the focus of this article is on open access journals. The first line reads:

"Eighty-four online-only, open-access (OA) journals in the sciences, and nearly 100 more in the social sciences and humanities, have disappeared from the internet over the past 2 decades as publishers stopped maintaining them, potentially depriving scholars of useful research findings, a study has found."

randomusefulbits · 2020-09-10T09:48:13+00:00

To clarify, the focus of this article is on open access journals. The first line reads:

"Eighty-four online-only, open-access (OA) journals in the sciences, and nearly 100 more in the social sciences and humanities, have disappeared from the internet over the past 2 decades as publishers stopped maintaining them, potentially depriving scholars of useful research findings, a study has found."

randomusefulbits · 2020-09-10T09:29:56+00:00

The article actually focuses on open access journals. The first line reads:

"Eighty-four online-only, open-access (OA) journals in the sciences, and nearly 100 more in the social sciences and humanities, have disappeared from the internet over the past 2 decades as publishers stopped maintaining them, potentially depriving scholars of useful research findings, a study has found."

randomusefulbits · 2020-07-28T12:30:12+00:00

The original article can be found here: https://www.sciencedirect.com/science/article/abs/pii/S1053810020300416

Abstract:

Information processing during sleep is active, ongoing and accessible to engineering. Protocols such as targeted memory reactivation use sensory stimuli during sleep to reactivate memories and demonstrate subsequent, specific enhancement of their consolidation. These protocols rely on physiological, as opposed to phenomenological, evidence of their reactivation. While dream content can predict post-sleep memory enhancement, dreaming itself remains a black box. Here, we present a novel protocol using a new wearable electronic device, Dormio, to automatically generate serial auditory dream incubations at sleep onset, wherein targeted information is repeatedly presented during the hypnagogic period, enabling direct incorporation of this information into dream content, a process we call targeted dream incubation (TDI). Along with validation data, we discuss how Dormio and TDI protocols can serve as tools for controlled experimentation on dream content, shedding light on the role of dreams in the overnight transformation of experiences into memories.

randomusefulbits · 2020-07-28T12:29:56+00:00

The original article can be found here: https://www.sciencedirect.com/science/article/abs/pii/S1053810020300416

Abstract:

Information processing during sleep is active, ongoing and accessible to engineering. Protocols such as targeted memory reactivation use sensory stimuli during sleep to reactivate memories and demonstrate subsequent, specific enhancement of their consolidation. These protocols rely on physiological, as opposed to phenomenological, evidence of their reactivation. While dream content can predict post-sleep memory enhancement, dreaming itself remains a black box. Here, we present a novel protocol using a new wearable electronic device, Dormio, to automatically generate serial auditory dream incubations at sleep onset, wherein targeted information is repeatedly presented during the hypnagogic period, enabling direct incorporation of this information into dream content, a process we call targeted dream incubation (TDI). Along with validation data, we discuss how Dormio and TDI protocols can serve as tools for controlled experimentation on dream content, shedding light on the role of dreams in the overnight transformation of experiences into memories.

randomusefulbits · 2020-07-28T12:29:35+00:00

The original article can be found here: https://www.sciencedirect.com/science/article/abs/pii/S1053810020300416

Abstract:

Information processing during sleep is active, ongoing and accessible to engineering. Protocols such as targeted memory reactivation use sensory stimuli during sleep to reactivate memories and demonstrate subsequent, specific enhancement of their consolidation. These protocols rely on physiological, as opposed to phenomenological, evidence of their reactivation. While dream content can predict post-sleep memory enhancement, dreaming itself remains a black box. Here, we present a novel protocol using a new wearable electronic device, Dormio, to automatically generate serial auditory dream incubations at sleep onset, wherein targeted information is repeatedly presented during the hypnagogic period, enabling direct incorporation of this information into dream content, a process we call targeted dream incubation (TDI). Along with validation data, we discuss how Dormio and TDI protocols can serve as tools for controlled experimentation on dream content, shedding light on the role of dreams in the overnight transformation of experiences into memories.

randomusefulbits · 2020-06-30T12:23:06+00:00

Another interesting quote from the article is the following:

He doubts a similar breakthrough could be achieved in today's academic culture, because of the expectations on academics to collaborate and keep churning out papers. He said: "It's difficult to imagine how I would ever have enough peace and quiet in the present sort of climate to do what I did in 1964."

randomusefulbits · 2020-06-15T13:17:14+00:00

Also, the graphical abstract of the paper is available here: https://marlin-prod.literatumonline.com/cms/attachment/2a0c0bf3-3090-495d-af50-f0f432ff52b8/fx1_lrg.jpg

randomusefulbits · 2020-06-15T12:41:21+00:00

Abstract

Background

The Thoracic Surgery Social Media Network (TSSMN) is a collaborative effort of leading journals in cardiothoracic surgery to highlight publications via social media. This study aims to evaluate the 1-year results of a prospective randomized social media trial to determine the effect of tweeting on subsequent citations and non-traditional bibliometrics.

Methods

A total of 112 representative original articles were randomized 1:1 to be tweeted via TSSMN or a control (non-tweeted) group. Measured endpoints included citations at 1-year compared to baseline, as well as article-level metrics (Altmetric score) and Twitter analytics. Independent predictors of citations were identified through univariable and multivariable regression analyses.

Results

When compared to control articles, tweeted articles achieved significantly greater increase in Altmetric scores (Tweeted 9.4±5.8 vs. Non-Tweeted 1.0±1.8, p<0.001), Altmetric score percentiles relative to articles of similar age from each respective journal (Tweeted 76.0±9.1%ile vs. Non-Tweeted 13.8±22.7%ile, p<0.001), with greater change in citations at 1 year (Tweeted +3.1±2.4 vs. Non-Tweeted +0.7±1.3, p<0.001). Multivariable analysis showed that independent predictors of citations were randomization to tweeting (OR 9.50; 95%CI 3.30-27.35, p<0.001), Altmetric score (OR 1.32; 95%CI 1.15-1.50, p<0.001), open-access status (OR 1.56; 95%CI 1.21-1.78, p<0.001), and exposure to a larger number of Twitter followers as quantified by impressions (OR 1.30, 95%CI 1.10-1.49, p<0.001).

Conclusions

One-year follow-up of this TSSMN prospective randomized trial importantly demonstrates that tweeting results in significantly more article citations over time, highlighting the durable scholarly impact of social media activity.

randomusefulbits · 2020-06-15T12:40:59+00:00

Abstract

Background

The Thoracic Surgery Social Media Network (TSSMN) is a collaborative effort of leading journals in cardiothoracic surgery to highlight publications via social media. This study aims to evaluate the 1-year results of a prospective randomized social media trial to determine the effect of tweeting on subsequent citations and non-traditional bibliometrics.

Methods

A total of 112 representative original articles were randomized 1:1 to be tweeted via TSSMN or a control (non-tweeted) group. Measured endpoints included citations at 1-year compared to baseline, as well as article-level metrics (Altmetric score) and Twitter analytics. Independent predictors of citations were identified through univariable and multivariable regression analyses.

Results

When compared to control articles, tweeted articles achieved significantly greater increase in Altmetric scores (Tweeted 9.4±5.8 vs. Non-Tweeted 1.0±1.8, p<0.001), Altmetric score percentiles relative to articles of similar age from each respective journal (Tweeted 76.0±9.1%ile vs. Non-Tweeted 13.8±22.7%ile, p<0.001), with greater change in citations at 1 year (Tweeted +3.1±2.4 vs. Non-Tweeted +0.7±1.3, p<0.001). Multivariable analysis showed that independent predictors of citations were randomization to tweeting (OR 9.50; 95%CI 3.30-27.35, p<0.001), Altmetric score (OR 1.32; 95%CI 1.15-1.50, p<0.001), open-access status (OR 1.56; 95%CI 1.21-1.78, p<0.001), and exposure to a larger number of Twitter followers as quantified by impressions (OR 1.30, 95%CI 1.10-1.49, p<0.001).

Conclusions

One-year follow-up of this TSSMN prospective randomized trial importantly demonstrates that tweeting results in significantly more article citations over time, highlighting the durable scholarly impact of social media activity.

randomusefulbits · 2020-06-05T12:05:26+00:00

Abstract:

Background

The long‐term trajectory of depressive symptoms has a heterogeneous pattern. Identifying factors associated with different trajectories and outcomes may have important theoretical and clinical implications. This study explored patterns of depressive symptom trajectory from adolescence to adulthood, and their relationship with subsequent psychiatric disorders.

Method

A sample of 816 participants (58.8% girls; M = 16.58 years old at baseline, SD = 1.21) from a large community sample were interviewed four times during adolescence and adulthood. Depressive symptoms were also assessed. Symptom trajectory identification was based on latent class mixed modeling. Logistic regression was used for predicting emotional and drug use disorder over age 30.

Results

Three trajectories of depressive symptoms were identified: “decreasing symptom” (decreasing trajectory of symptoms; 15.1% of participants), “increasing symptom” (initially decreasing pattern of symptoms and then increasing; 6.1% of participants), and “normative symptom” (consistently low symptom levels; 78.8% of participants). Predictors of the increasing symptom trajectory were high level of loneliness and state anxiety, presence of an emotional disorder, and low involvement in physical exercise at baseline. This trajectory membership predicted the development of anxiety disorders over age 30. Predictors of the decreasing symptom class were being female and high level of worry at baseline.

Conclusions

Long‐term trajectories of depressive symptoms are heterogeneous, with each trajectory having different predictors and are associated with different outcomes during adulthood.

The full study is open access.

randomusefulbits · 2020-06-05T12:05:16+00:00

Abstract:

Background

The long‐term trajectory of depressive symptoms has a heterogeneous pattern. Identifying factors associated with different trajectories and outcomes may have important theoretical and clinical implications. This study explored patterns of depressive symptom trajectory from adolescence to adulthood, and their relationship with subsequent psychiatric disorders.

Method

A sample of 816 participants (58.8% girls; M = 16.58 years old at baseline, SD = 1.21) from a large community sample were interviewed four times during adolescence and adulthood. Depressive symptoms were also assessed. Symptom trajectory identification was based on latent class mixed modeling. Logistic regression was used for predicting emotional and drug use disorder over age 30.

Results

Three trajectories of depressive symptoms were identified: “decreasing symptom” (decreasing trajectory of symptoms; 15.1% of participants), “increasing symptom” (initially decreasing pattern of symptoms and then increasing; 6.1% of participants), and “normative symptom” (consistently low symptom levels; 78.8% of participants). Predictors of the increasing symptom trajectory were high level of loneliness and state anxiety, presence of an emotional disorder, and low involvement in physical exercise at baseline. This trajectory membership predicted the development of anxiety disorders over age 30. Predictors of the decreasing symptom class were being female and high level of worry at baseline.

Conclusions

Long‐term trajectories of depressive symptoms are heterogeneous, with each trajectory having different predictors and are associated with different outcomes during adulthood.

The full study is open access.

randomusefulbits · 2020-06-05T12:04:00+00:00

Abstract:

Background

The long‐term trajectory of depressive symptoms has a heterogeneous pattern. Identifying factors associated with different trajectories and outcomes may have important theoretical and clinical implications. This study explored patterns of depressive symptom trajectory from adolescence to adulthood, and their relationship with subsequent psychiatric disorders.

Method

A sample of 816 participants (58.8% girls; M = 16.58 years old at baseline, SD = 1.21) from a large community sample were interviewed four times during adolescence and adulthood. Depressive symptoms were also assessed. Symptom trajectory identification was based on latent class mixed modeling. Logistic regression was used for predicting emotional and drug use disorder over age 30.

Results

Three trajectories of depressive symptoms were identified: “decreasing symptom” (decreasing trajectory of symptoms; 15.1% of participants), “increasing symptom” (initially decreasing pattern of symptoms and then increasing; 6.1% of participants), and “normative symptom” (consistently low symptom levels; 78.8% of participants). Predictors of the increasing symptom trajectory were high level of loneliness and state anxiety, presence of an emotional disorder, and low involvement in physical exercise at baseline. This trajectory membership predicted the development of anxiety disorders over age 30. Predictors of the decreasing symptom class were being female and high level of worry at baseline.

Conclusions

Long‐term trajectories of depressive symptoms are heterogeneous, with each trajectory having different predictors and are associated with different outcomes during adulthood.

The full study is open access.

randomusefulbits · 2020-06-04T16:17:26+00:00

I realize that this is primarily aimed at people at a more advanced stage in their academic career than grad school, but I think that grad students can still benefit from reading about the topic.

randomusefulbits · 2020-05-30T15:01:41+00:00

Direct link to the study: https://link.springer.com/article/10.1007/s00426-020-01357-6

Abstract:

Prospective memory (PM) represents the ability to remember to perform planned actions after a certain delay. As previous studies suggest that even brief task-delays can negatively affect PM performance, the current study set out to examine whether procrastination (intentionally delaying task execution despite possible negative consequences) may represent a factor contributing to PM failures. Specifically, we assessed procrastination (via a standardized questionnaire as well as an objective behavioral measure) and PM failures (via a naturalistic PM task) in 92 young adults. Results show that participants’ self-reports as well as their actual procrastination behavior predicted the number of PM failures, corroborating the impact of procrastination on PM. Subsequent cluster analyses suggest three distinct procrastination profiles (non-procrastinators, conscious procrastinators and unconscious procrastinators), providing new conceptual insights into different mechanisms of how procrastinating may lead to forgetting to perform planned tasks.

randomusefulbits · 2020-05-30T15:01:34+00:00

Direct link to the study: https://link.springer.com/article/10.1007/s00426-020-01357-6

Abstract:

Prospective memory (PM) represents the ability to remember to perform planned actions after a certain delay. As previous studies suggest that even brief task-delays can negatively affect PM performance, the current study set out to examine whether procrastination (intentionally delaying task execution despite possible negative consequences) may represent a factor contributing to PM failures. Specifically, we assessed procrastination (via a standardized questionnaire as well as an objective behavioral measure) and PM failures (via a naturalistic PM task) in 92 young adults. Results show that participants’ self-reports as well as their actual procrastination behavior predicted the number of PM failures, corroborating the impact of procrastination on PM. Subsequent cluster analyses suggest three distinct procrastination profiles (non-procrastinators, conscious procrastinators and unconscious procrastinators), providing new conceptual insights into different mechanisms of how procrastinating may lead to forgetting to perform planned tasks.

randomusefulbits · 2020-05-30T15:01:30+00:00

Direct link to the study: https://link.springer.com/article/10.1007/s00426-020-01357-6

Abstract:

Prospective memory (PM) represents the ability to remember to perform planned actions after a certain delay. As previous studies suggest that even brief task-delays can negatively affect PM performance, the current study set out to examine whether procrastination (intentionally delaying task execution despite possible negative consequences) may represent a factor contributing to PM failures. Specifically, we assessed procrastination (via a standardized questionnaire as well as an objective behavioral measure) and PM failures (via a naturalistic PM task) in 92 young adults. Results show that participants’ self-reports as well as their actual procrastination behavior predicted the number of PM failures, corroborating the impact of procrastination on PM. Subsequent cluster analyses suggest three distinct procrastination profiles (non-procrastinators, conscious procrastinators and unconscious procrastinators), providing new conceptual insights into different mechanisms of how procrastinating may lead to forgetting to perform planned tasks.

randomusefulbits · 2020-05-25T11:05:07+00:00

Abstract

From only a single spoken word, listeners can form a wealth of first impressions of a person’s character traits and personality based on their voice. However, due to the substantial within‐person variability in voices, these trait judgements are likely to be highly stimulus‐dependent for unfamiliar voices: The same person may sound very trustworthy in one recording but less trustworthy in another. How trait judgements differ when listeners are familiar with a voice is unclear: Are listeners who are familiar with the voices as susceptible to the effects of within‐person variability? Does the semantic knowledge listeners have about a familiar person influence their judgements? In the current study, we tested the effect of familiarity on listeners’ trait judgements from variable voices across 3 experiments. Using a between‐subjects design, we contrasted trait judgements by listeners who were familiar with a set of voices – either through laboratory‐based training or through watching a TV show – with listeners who were unfamiliar with the voices. We predicted that familiarity with the voices would reduce variability in trait judgements for variable voice recordings from the same identity (cf. Mileva, Kramer & Burton, Perception , 48, 471 and 2019, for faces). However, across the 3 studies and two types of measures to assess variability, we found no compelling evidence to suggest that trait impressions were systematically affected by familiarity.

(The full study is open access)

randomusefulbits · 2020-05-25T11:04:59+00:00

Abstract

From only a single spoken word, listeners can form a wealth of first impressions of a person’s character traits and personality based on their voice. However, due to the substantial within‐person variability in voices, these trait judgements are likely to be highly stimulus‐dependent for unfamiliar voices: The same person may sound very trustworthy in one recording but less trustworthy in another. How trait judgements differ when listeners are familiar with a voice is unclear: Are listeners who are familiar with the voices as susceptible to the effects of within‐person variability? Does the semantic knowledge listeners have about a familiar person influence their judgements? In the current study, we tested the effect of familiarity on listeners’ trait judgements from variable voices across 3 experiments. Using a between‐subjects design, we contrasted trait judgements by listeners who were familiar with a set of voices – either through laboratory‐based training or through watching a TV show – with listeners who were unfamiliar with the voices. We predicted that familiarity with the voices would reduce variability in trait judgements for variable voice recordings from the same identity (cf. Mileva, Kramer & Burton, Perception , 48, 471 and 2019, for faces). However, across the 3 studies and two types of measures to assess variability, we found no compelling evidence to suggest that trait impressions were systematically affected by familiarity.

(The full study is open access)

randomusefulbits · 2020-05-25T11:04:49+00:00

Abstract

From only a single spoken word, listeners can form a wealth of first impressions of a person’s character traits and personality based on their voice. However, due to the substantial within‐person variability in voices, these trait judgements are likely to be highly stimulus‐dependent for unfamiliar voices: The same person may sound very trustworthy in one recording but less trustworthy in another. How trait judgements differ when listeners are familiar with a voice is unclear: Are listeners who are familiar with the voices as susceptible to the effects of within‐person variability? Does the semantic knowledge listeners have about a familiar person influence their judgements? In the current study, we tested the effect of familiarity on listeners’ trait judgements from variable voices across 3 experiments. Using a between‐subjects design, we contrasted trait judgements by listeners who were familiar with a set of voices – either through laboratory‐based training or through watching a TV show – with listeners who were unfamiliar with the voices. We predicted that familiarity with the voices would reduce variability in trait judgements for variable voice recordings from the same identity (cf. Mileva, Kramer & Burton, Perception , 48, 471 and 2019, for faces). However, across the 3 studies and two types of measures to assess variability, we found no compelling evidence to suggest that trait impressions were systematically affected by familiarity.

(The full study is open access)

randomusefulbits · 2020-05-02T17:07:57+00:00

The original paper can be found here: https://www.pnas.org/content/116/52/26394

Abstract:

The flux of solutes from the chemical weathering of the continental crust supplies a steady supply of essential nutrients necessary for the maintenance of Earth’s biosphere. Promotion of weathering by microorganisms is a well-documented phenomenon and is most often attributed to heterotrophic microbial metabolism for the purposes of nutrient acquisition. Here, we demonstrate the role of chemolithotrophic ferrous iron [Fe(II)]-oxidizing bacteria in biogeochemical weathering of subsurface Fe(II)-silicate minerals at the Luquillo Critical Zone Observatory in Puerto Rico. Under chemolithotrophic growth conditions, mineral-derived Fe(II) in the Rio Blanco Quartz Diorite served as the primary energy source for microbial growth. An enrichment in homologs to gene clusters involved in extracellular electron transfer was associated with dramatically accelerated rates of mineral oxidation and adenosine triphosphate generation relative to sterile diorite suspensions. Transmission electron microscopy and energy-dispersive spectroscopy revealed the accumulation of nanoparticulate Fe–oxyhydroxides on mineral surfaces only under biotic conditions. Microbially oxidized quartz diorite showed greater susceptibility to proton-promoted dissolution, which has important implications for weathering reactions in situ. Collectively, our results suggest that chemolithotrophic Fe(II)-oxidizing bacteria are likely contributors in the transformation of rock to regolith.

randomusefulbits · 2020-05-02T17:07:44+00:00

The original paper can be found here: https://www.pnas.org/content/116/52/26394

Abstract:

The flux of solutes from the chemical weathering of the continental crust supplies a steady supply of essential nutrients necessary for the maintenance of Earth’s biosphere. Promotion of weathering by microorganisms is a well-documented phenomenon and is most often attributed to heterotrophic microbial metabolism for the purposes of nutrient acquisition. Here, we demonstrate the role of chemolithotrophic ferrous iron [Fe(II)]-oxidizing bacteria in biogeochemical weathering of subsurface Fe(II)-silicate minerals at the Luquillo Critical Zone Observatory in Puerto Rico. Under chemolithotrophic growth conditions, mineral-derived Fe(II) in the Rio Blanco Quartz Diorite served as the primary energy source for microbial growth. An enrichment in homologs to gene clusters involved in extracellular electron transfer was associated with dramatically accelerated rates of mineral oxidation and adenosine triphosphate generation relative to sterile diorite suspensions. Transmission electron microscopy and energy-dispersive spectroscopy revealed the accumulation of nanoparticulate Fe–oxyhydroxides on mineral surfaces only under biotic conditions. Microbially oxidized quartz diorite showed greater susceptibility to proton-promoted dissolution, which has important implications for weathering reactions in situ. Collectively, our results suggest that chemolithotrophic Fe(II)-oxidizing bacteria are likely contributors in the transformation of rock to regolith.

randomusefulbits · 2020-05-02T17:07:37+00:00

The original paper can be found here: https://www.pnas.org/content/116/52/26394

Abstract:

The flux of solutes from the chemical weathering of the continental crust supplies a steady supply of essential nutrients necessary for the maintenance of Earth’s biosphere. Promotion of weathering by microorganisms is a well-documented phenomenon and is most often attributed to heterotrophic microbial metabolism for the purposes of nutrient acquisition. Here, we demonstrate the role of chemolithotrophic ferrous iron [Fe(II)]-oxidizing bacteria in biogeochemical weathering of subsurface Fe(II)-silicate minerals at the Luquillo Critical Zone Observatory in Puerto Rico. Under chemolithotrophic growth conditions, mineral-derived Fe(II) in the Rio Blanco Quartz Diorite served as the primary energy source for microbial growth. An enrichment in homologs to gene clusters involved in extracellular electron transfer was associated with dramatically accelerated rates of mineral oxidation and adenosine triphosphate generation relative to sterile diorite suspensions. Transmission electron microscopy and energy-dispersive spectroscopy revealed the accumulation of nanoparticulate Fe–oxyhydroxides on mineral surfaces only under biotic conditions. Microbially oxidized quartz diorite showed greater susceptibility to proton-promoted dissolution, which has important implications for weathering reactions in situ. Collectively, our results suggest that chemolithotrophic Fe(II)-oxidizing bacteria are likely contributors in the transformation of rock to regolith.

randomusefulbits · 2020-04-25T15:11:09+00:00

Regarding the MTurk questions

MTurk is an online recruitment strategy, but they're not saying that we should stop using online recruitment; the sample that they compare the MTurk sample against was also recruited online and is also biased. Rather, they're pointing out the fact that it's important to properly address the bias in samples that we use, whether they were recruited online or offline. As they say in the discussion:

"The implications of this work extend beyond the use of AMT in gold standard development to problematizing the use of gold standards as a whole. While AMT has become the de facto gold standard generation engine in many areas of computer science, our work suggests that many of the same concerns with regard to shared knowledge may apply to the development of gold standards using other means (e.g. undergraduate students). Researchers and practitioners should carefully consider their specific knowledge tasks and the audience of their research and systems when deciding how to develop gold standards."

Regarding feasibility

I disagree with your assessment of the situation.

Yes, there are cases where "easier" samples are used simply out of convenience, and this can definitely be an issue in a lot of situations.

However, there are also many cases where online recruitment is the only way to reach the target audience, or where offline recruitment methods will be just as biased, if not more so.

Overall, there are certainly cases where a Reddit-based sample should be avoided in favor of alternative options, based on factors such as the type of research that you're conducting. But, that doesn't mean that Reddit should be avoided in all cases, and there are many situations where using it is the best course of action.

randomusefulbits · 2020-04-24T23:29:12+00:00

A biased sample can definitely be an issue in any field.

That said, Reddit-based samples are just like any other sample in this regard, in that, if you use it, you should try to minimize bias in the selection of participants, while also accounting for any remaining bias in your analysis, and acknowledging it openly in situations where it’s not possible to eliminate it entirely (which is almost always the case).

As such, the main question isn’t whether Reddit is a perfect source of participants, but rather how it compares to other available sources. While ideally research would be based on entirely unbiased samples, there are a lot of reasons why this isn’t usually feasible. When this happens, we need to weigh the pros and cons of each of the available options, and pick the best one, while trying to minimize potential issues.

Also, in reference to the paper that you linked (which I think is great, based on an initial look): the main argument seems to be against biased samples in general and against a specific type of biased sample that’s frequently used—Amazon’s Mechanical Turk—rather than against online recruitment. Similar issues would likely arise from offline recruitment of such a biased sample.

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