Interpretation of the bystander effect

[rlaboss]

Does the bystander effect necessarily mean that a person is less likely to be helped when many people are around, or does it only describe the phenomenon that a person is less likely to help when others are around. Based on the aamc sample FL P/S #45, it seems like the AAMC has interpreted the bystander effect as someone is less likely to be helped when many people are around. Can I expect this interpretation of the theory to be consistent with the real MCAT? Thanks

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[aldol16]

Those two statements are two sides of the same coin. If a person is less likely to be helped when there are many bystanders, it directly follows that if a person is a bystander with many people around, they're also less likely to help out.

 

[rlaboss]

Those two statements are two sides of the same coin. If a person is less likely to be helped when there are many bystanders, it directly follows that if a person is a bystander with many people around, they're also less likely to help out.

For example, say there is a 90% chance any given person will help someone if they are the only two people present. If that likelihood drops to 10% if there are 100 people present, the chance that no one help is 0.90^100 = 0.0000266 = 0.00266% that no one will help. Therefore there is a ~100% chance at least one person will help.

 

[rlaboss]

For example, say there is a 90% chance any given person will help someone if they are the only two people present. If that likelihood drops to 10% if there are 100 people present, the chance that no one help is 0.90^100 = 0.0000266 = 0.00266% that no one will help. Therefore there is a ~100% chance at least one person will help.

Those two statements are two sides of the same coin. If a person is less likely to be helped when there are many bystanders, it directly follows that if a person is a bystander with many people around, they're also less likely to help out.

Just because someone is less likely to help doesn't mean the person that needs help is less likely to be helped

 

[663697]

Just because someone is less likely to help doesn't mean the person that needs help is less likely to be helped

Well it's assumed that the diffusion of responsibility is not just felt by one person, but by most/all the people in the vicinity. So if everyone defers responsibility to the other people around them, nobody takes action and the person becomes less likely to be helped.

 

[rlaboss]

Well it's assumed that the diffusion of responsibility is not just felt by one person, but by most/all the people in the vicinity. So if everyone defers responsibility to the other people around them, nobody takes action and the person becomes less likely to be helped.

I understand that IF the person is less likely to be helped in a situation with more people it is because everyone else must feel the diffusion of responsibility. Would my example explained earlier in the threat be considered the bystander effect? Although each individual is less likely to help, the increased number of people results in an increased likelihood that at least one person will help.

"For example, say there is a 90% chance any given person will help someone if they are the only two people present. If that likelihood drops to 10% if there are 100 people present, the chance that no one help is 0.90^100 = 0.0000266 = 0.00266% that no one will help. Therefore there is a ~100% chance at least one person will help."

 

[663697]

I understand that IF the person is less likely to be helped in a situation with more people it is because everyone else must feel the diffusion of responsibility. Would my example explained earlier in the threat be considered the bystander effect? Although each individual is less likely to help, the increased number of people results in an increased likelihood that at least one person will help.

"For example, say there is a 90% chance any given person will help someone if they are the only two people present. If that likelihood drops to 10% if there are 100 people present, the chance that no one help is 0.90^100 = 0.0000266 = 0.00266% that no one will help. Therefore there is a ~100% chance at least one person will help."

Well, if you use the same reasoning for your example, then the chance that someone helps out of 100 people is 0.1^100, which is even less than 0.00266%. I don't think you can just calculate it that way though, there are a lot of other factors involved that would probably have to be incorporated into a more sophisticated mathematical model, assuming that you can even model it.

 

[rlaboss]

Well, if you use the same reasoning for your example, then the chance that someone helps out of 100 people is 0.1^100, which is even less than 0.00266%. I don't think you can just calculate it that way though, there are a lot of other factors involved that would probably have to be incorporated into a more sophisticated mathematical model, assuming that you can even model it.

Obviously there are other factors but if every person has a 10% chance of helping out, there is a 0.0026% chance that nobody will help. Therefore its almost certain at least one person will help.

 

[rlaboss]

Well, if you use the same reasoning for your example, then the chance that someone helps out of 100 people is 0.1^100, which is even less than 0.00266%. I don't think you can just calculate it that way though, there are a lot of other factors involved that would probably have to be incorporated into a more sophisticated mathematical model, assuming that you can even model it.

It doesn't really matter. I guess just know that AAMC interprets it that in a situation with more people around, the person in need of help is less likely to get help.

 

[rabbott1971]

The bystander effect works upon third parties, not the one in distress. The bystander effect reduces the likelihood that a particular person will render aid. This would reduce the overall chances for the person in distress to be aided, but the person in distress is not experiencing the bystander effect. Calculations are not needed.

 

[rlaboss]

The bystander effect works upon third parties, not the one in distress. The bystander effect reduces the likelihood that a particular person will render aid. This would reduce the overall chances for the person in distress to be aided, but the person in distress is not experiencing the bystander effect. Calculations are not needed.

It could reduce the overall chance that the person receives aid, but not necessarily, as explained by the calculations. Simply put, the increase in the number of bystanders, each with a given likelihood to help, could overcome the decrease of each particular person giving help.

 

[663697]

It could reduce the overall chance that the person receives aid, but not necessarily, as explained by the calculations. Simply put, the increase in the number of bystanders, each with a given likelihood to help, could overcome the decrease of each particular person giving help.

You can't just calculate it like that though. You are assuming a binomial distribution where each test is independent of the other, but think about what happens as you actually increase the number of people -- p and q change. If that's not convincing enough just search up real life examples which show that people usually don't step in to help (keep in mind, it's not saying nobody will ever help).

 

[rabbott1971]

It could reduce the overall chance that the person receives aid, but not necessarily, as explained by the calculations. Simply put, the increase in the number of bystanders, each with a given likelihood to help, could overcome the decrease of each particular person giving help.

This is why I said calculations are not needed. Because as @Cuttlefish keeps saying, you don't know the variables or the rate of change in likelihood of rendering aid as crowd size increases.

Your original post said "MCAT" so the answers you are getting are framed in terms of the MCAT. The bystander effect reduces the likelihood of a third party rendering aid to a person in distress, thereby generally reducing the likelihood that the person in distress receives aid, as @aldol16 said. Just because you can create a calculation purporting to show the opposite doesn't make it true, and it certainly isn't useful MCAT prep.

 

[rlaboss]

This is why I said calculations are not needed. Because as @Cuttlefish keeps saying, you don't know the variables or the rate of change in likelihood of rendering aid as crowd size increases.

Your original post said "MCAT" so the answers you are getting are framed in terms of the MCAT. The bystander effect reduces the likelihood of a third party rendering aid to a person in distress, thereby generally reducing the likelihood that the person in distress receives aid, as @aldol16 said. Just because you can create a calculation purporting to show the opposite doesn't make it true, and it certainly isn't useful MCAT prep.

In terms of the MCAT and the AAMC's perspective, you're right. The problem I have is I just don't see how it's absolutely true that the person is less likely to receive help. Yes each person present is less likely to help, but how can say whether the person in distress is less likely or more likely to be helped with more people present. The calculation is to show that both are possible

 

[aldol16]

Please look up examples of the bystander effect. Most if not all of the examples result in the victim not being helped as a result of the bystander effect.