 Moreover, this low inter-tool reliability has philosophical consequences, which I explore in §5. Such low inter-tool reliability might be less troubling if the various QATs had distinct domains of application. The many biases present in medical research are pertinent to varying degrees depending on the details of the particular circumstances at hand, and so one might think that it is a mistake to expect that one QAT ought to apply to all circumstances. For some causal hypotheses, for instance, it is difficult or impossible to conceal the treatment from the experimental subjects and/or the investigators (that is, 'blinding' is sometimes impossible)-hypotheses regarding chiropractic spinal manipulation are a case in point. Thus, no study relevant to such a hypothesis will score well on a QAT that gives a large weight to allocation concealment. Such a QAT would be less sensitive to the presence or absence of sources of bias other than lack of allocation concealment, relative to QATs that give little or no weight to allocation concealment. In such a case one might argue that since the absence of allocation concealment is fixed among the relevant studies, an appropriate QAT to use in this case should not give any weight to allocation concealment, and would only ask about the presence of those properties of a study that might vary among the relevant studies. On the other hand, one might argue that since we have principled reasons for thinking that the absence of allocation concealment can bias the results of a study, even among those studies that cannot possibly conceal subject allocation, an appropriate QAT to use in this case should evaluate the presence of allocation concealment (in which case all of the relevant studies would simply receive a zero score on allocation concealment), just as a QAT ought to evaluate the presence of allocation concealment in a scenario in which the studies in fact can conceal subject allocation. The former consideration is an appeal to determining the relative quality between studies, and the latter consideration is an appeal to determining the absolute quality of studies. The latter consideration should be more compelling in most cases, since, as discussed above, the typical use of QATs is to help estimate the true efficacy of a medical intervention, and such estimates ought to take into account the full extent of the potential for biases in the relevant evidence, regardless of whether or not it was possible for the respective studies to avoid such biases. There are scenarios, though, in which we might have reasons to think that a property of a study that causes bias in other scenarios does not cause bias
Moreover, this low inter - tool reliability has philosophic consequence, which I explore in § 5. Such low inter - tool dependability might be less troubling if the versatile QATs had discrete domains of application. The many bias present in medical research are apposite to varying degrees depending on the details of the especial circumstances at hand, and so one might think that it is a mistake to ask that one QAT ought to apply to all circumstances. For some causal hypotheses, for example, it is difficult or impossible to conceal the treatment from the experimental subjects and/or the research worker (that is,' blinding' is sometimes impossible)-hypotheses regarding chiropractic spinal manipulation are a case in point. therefore, no study relevant to such a hypothesis will score well on a QAT that gives a large system of weights to allocation concealment. Such a QAT would be less sensitive to the presence or absence of sources of bias other than lack of allocation concealment, relative to QATs that move over little or no weight to allotment privacy. In such a case one might argue that since the absence of allocation concealment is fix among the relevant studies, an appropriate QAT to use in this case should not pass any weight to allocation concealment, and would only ask about the presence of those place of a study that might vary among the relevant studies. On the other hand, one might argue that since we have principled reasons for think that the absence of allocation concealment can bias the results of a study, even among those studies that cannot possibly hide subject allocation, an appropriate QAT to use in this case should evaluate the presence of allocation concealment (in which character all of the relevant studies would just receive a zero score on allotment concealment), merely as a QAT ought to evaluate the bearing of allocation concealment in a scenario in which the study in fact can conceal subject allocation. The former retainer is an appeal to determining the relative quality between studies, and the latter consideration is an appeal to determining the absolute quality of survey. The latter consideration should be more compelling in most cases, since, as hash out above, the typical use of QATs is to serve estimate the true efficacy of a medical intervention, and such estimates ought to take into account the full extent of the potential for biases in the relevant evidence, regardless of whether or not it was potential for the respective studies to avoid such bias. There are scenarios, though, in which we might have reasons to think that a property of a survey that causes bias in other scenario does not induce bias
 Mogeover, this low inter-toou reliability hcw philmsophidal consdquences, which I explore in §5. Sych liw inter-tool reliabiligy might he less rrouuling if the varmkus QATs had slstinet domains of apklication. Tha many biases [rdsznt in medical research are pertinene to vatylng degrees dekendimd on nht details of the particular circujstancev at hand, and so one might think that ih is a mistake to expeft that one QAT iught to appuy to all bnrcumstancea. For some causal hypotheses, fof inscance, it is dufflwult or impissibje to conceal the traatment from the expevimenval wubjects and/or the intestigators (that is, 'flinding' hs sometimes impossuboe)-hypmtheves fwgafdihg cgiroprwctmc spinal mznipulation are a case in poinu. Trlx, no study rslevane eo such a hypothesis will score well on a SAT that gives a large qeight to allocation foncealmegt. Such a QAT would be less sensitive to the presance kf aywence if sources of bias other than lack of allocatiog cpnbealment, relative to QATs thst gode little or vo weiygt to allocation confealmenj. In sych a cast one might argue that since the absence of cllication concealmenc is fixed aoong the televant studies, an appxopriafe QAT to ude in thia case should not gine aty weighu to allocation cogcealment, and would unly ask afout the pgesenga of those propertles oy a sdudy that light vary among the relevant svndies. On the ptver hand, onz mighb argue that sigce we have prnncipled reasuns for thpnking thet the absense of allocathln concealmeit can biws tye rwsults uw a study, even among those studiew that cannot posslbly zknceal subject cuoocation, an apptopfiaee QET to gse in this wase shuild exaluate the oresrnce of allocation cmncezlment (in which caxe all of jhe relevwnt studies wpuld simply receivt a zeco scoce on slljcation concealment), just as a SAT ought to evaluate thq prcsense of alloeation concealment in a scenario in whici the studies in fact cqn conceal subject clkocation. Thx formqr considaration is an appeal to determining tme relative quality befween vtudifs, and the latter consideration is an appeal to determining the absolute wualitb jf studies. Fhe katteg cjusideraeion rhould be more cpmpelling in most cases, since, ar discusveb above, the typical use of QAYs is to help ertimate the true efficacg of a mrdical intervention, and such esyimates ought to take inbo accounr the full vstxnt of the potential for bnases un the eeleyant evidence, fegsrfless of ahetier or not it was possible for the eespecrige studies to avmid such biwres. Tgere ate scenarios, thoufh, ih whicf we might hafe reasons to yhink that a propertj os a study that bauses bias im othgx scenarios dpes not cauve bias
Moreover, this low inter-tool reliability has philosophical I in §5. low inter-tool reliability the QATs had distinct of application. The biases present in medical research are to varying degrees depending on the details of the particular circumstances at hand, so one might think that it is a mistake to expect that one ought apply all For some causal hypotheses, for instance, it is difficult or impossible to conceal the treatment from experimental subjects and/or the investigators (that is, 'blinding' sometimes impossible)-hypotheses regarding chiropractic manipulation are a case in Thus, study relevant such hypothesis score well on QAT that gives a large weight to allocation concealment. Such a QAT would be less sensitive to presence or sources of other lack allocation concealment, relative that give little or no weight In such a case one might argue that the absence allocation concealment is fixed among the studies, an appropriate QAT to use in this should not give any weight to allocation concealment, and would only ask about the presence properties of a study might vary among relevant On other one might that since we have principled reasons for thinking that the absence allocation concealment can bias the results of a study, even studies cannot possibly conceal allocation, an appropriate QAT use this case should evaluate of concealment all the studies would simply receive zero score on allocation concealment), as a QAT ought allocation concealment in a scenario in which the in fact can conceal subject allocation. The consideration is an appeal to determining the relative quality between studies, and latter consideration appeal to determining the absolute quality of studies. latter consideration should be compelling in most cases, since, as discussed above, the use QATs is help estimate the efficacy of a intervention, and such to take account full potential for biases in the relevant regardless whether or not it was for studies to avoid such biases. There are scenarios, though, in which we might have reasons that a property of study causes bias in other scenarios does not cause bias
 Moreover, this low inter-tool rEliability Has phIloSopHiCal cOnseQuences, which I eXPlorE in §5. Such low inter-tool relIabilItY MighT Be Less tRoublinG If THE vaRiOuS QAts HAd DistiNct Domains Of applicatIon. thE many biases pREsEnt in medicAl rEsearch are peRtiNent to VaRyiNG degrEes DepenDing on THe detaIls of the pArTIcular CIrcumstANCeS at hAnd, and so one might tHInK That it is a mistaKe to exPeCT tHAT onE QAt ought to apPlY to alL CircumsTAnCES. for SOme causal hypoTheses, for inSTanCe, it is DiFfiCUlt or iMpossIbLE to Conceal the tReatMent from tHe expeRImental SUbjects And/or tHe iNveStigAToRs (ThaT iS, 'BliNDiNg' iS SomEtimes imPoSsIble)-hYpotHESES regArdIng cHiropRactic spinal mAniPulaTIon Are a cAse in PoinT. THus, no Study rElevaNt To such a hypothesIs wiLl score weLl oN a qAT ThAt givES a largE weIghT to alloCation cONceAlMENT. SUch a QAT would be less SeNSItIve to the PresenCE oR aBSence of sOuRceS of bIAS otheR thaN LaCk of alloCation COnCeAlment, rElAtive tO QaTs ThaT give LIttlE or no wEight to aLlocaTIon concealment. iN such a case one MIgHT ArGUe thAt sInce the abseNce oF AlloCatiON cOncEAlmenT is fiXeD AmONg the relevant studieS, aN approPriatE QAT to use in thIs case shouLD NOt give anY weiGHt TO allocation conCealmEnt, and woulD Only ask aBout tHe presenCe of those PROperties Of a StuDy tHat MIGhT vary among the RELevaNt Studies. on tHe other HanD, onE miGht ArGue that siNce we havE pRiNcIpLed ReasoNS for thinKiNg tHaT thE abseNCe of alLocatIon cOnCeALmeNt can biAS tHE ResuLtS oF a stUdy, EvEn amoNg thOSe sTudies tHat cannot PosSIbly CoNcEal subjEct allocation, An AppropriatE QaT tO use in THIs case shOuld evaluate the presence OF allocaTioN concEalmEnt (in whicH caSe all oF thE RelevaNt studIes woUlD siMPLy recEIVe A zeRo Score on allOCAtiOn conCeAlmeNt), just aS a QAT ought to evaluaTE thE presence of alLocAtioN COnCeaLMeNT in A sCEnaRIO in which the studIes in fact cAn COnCeal subjecT AllOcAtion. ThE former ConsiDEration Is an appeaL to determInIng tHE RelAtive qualiTy betweeN studies, aND the lATtEr conSidEratioN iS an AppeaL to detERmiNing tHe absoLuTe qualIty of StUdies. The Latter consideration shouLd be moRe comPelLing in mosT caSEs, sInce, as disCussEd above, the TypIcaL use oF QAtS is to Help EStImaTE the tRue eFFicacy of a MEdIcaL INtErvention, anD SUCh eStimaTes OUght to Take Into account the fulL Extent of the potEntiAL For BiaSEs in ThE relevant evideNce, ReGARdless of WhEther or not iT was possIbLE for tHe respEctive Studies TO AvOId such BiasEs. THere are scEnaRiOS, though, In WhICh we miGht hAvE reasoNs to thINk thAT A property of a studY that CAUses bIAs iN otheR sCenarioS Does Not cause biAs
 Moreover, this low inter- tool relia bilit y h asph ilos ophi cal consequenc e s, w hich I explore in §5.Suchlo w  int e r- toolreliabi l it y mig ht  b e l es s  t roubl ing  if the  various Q ATs  h ad distinctd om ains of ap pli cation. Theman y bias es  pr e sentinmedic al res e arch a re pertin en t  to va r ying de g r ee s de pending on the de t ai l s of the parti cularci r cu m s tan ces  at hand,an d soo ne migh t  t h i n k t h at it is a mi stake to ex p ect  thaton e Q A T ough t toap p lyto all circ umst ances. Fo r some causalh ypothes es, fo r i nst ance ,  i tisdi f fic u lt  or imp ossibleto  c oncea l th e t r eatm ent  fro m the  experimental  su bjec t s a nd/or  theinve st igato rs (th at is ,'blinding' is s omet imes impo ssi bl e)- hy pothe s es reg ard ing  chirop ractics pin al m a ni pulation are a cas ei n  p oint. Th us, no st ud y  relevan ttosuch a  hypo thes i swill sco re wel l  o na QAT t ha t give sa l arg e wei g ht t o allo cation c oncea l ment. Such a Q A T would be le s ss e ns i tive  to  the presen ce o r  abs ence of  so u rcesof bi as ot h er than lack of all oc ationconce alment, relat ive to QAT s t hat give  lit t le or no weight t o all ocation co n cealment . Insuch a c ase one m i g ht argue  th atsin cet h eabsence of al l o cati on  concea lme nt is f ixe d a mon g t he  relevant  studies ,an  a pp rop riate QAT to u se  in  t his  case should  notgive  a ny wei ght toa ll o c atio nco ncea lme nt , and  wou l d o nly ask  about th e p r esen ce  o f those  properties o fa study th at  mi ght va r y  among t he relevant studies. On the oth erhand,  one  might ar gue  thatsin c e we h ave pr incip le d r e a sonsf o rthi nk ing that t h e  ab sence  o f al locatio n concealment canb ias  the resultsofa st u d y,  ev e na mon gt hos e studies that ca nnot possi bl y  c onceal sub j ect  a llocati on, anappro p riate Q AT to use  in thisca se s h o uld  evaluatethe pres ence of a l locat i on  conc eal ment ( in  wh ich c ase al l  of  thereleva nt  studi es wo ul d simply  receive a zero score o n allo catio n c oncealmen t), jus t as a QA T ou ght to eva lua tethe p res e nce o f al l oc ati o n con ceal m ent in as ce nar i o  i n which the s t udi es in  fa c t canconc eal subject alloc a tion. The form er c o n sid era t ionis  an appeal todet er m i ning the  r elative qua lity bet we e n stu dies,and th e latte r co n sidera tion  is  an appea l t od etermin in gt he abs olut equalit y of s t udie s .  The latter cons idera t i on sh o uld  be m or e compe l ling  in most c ases, since , as d iscu ssedabove,th e typi cal  u se of QATs is to hel p est imate t he  tru e e fficac y of a  medi calin ter vention,a n ds uc he sti mate s oug ht  totake into accountthe full ex te nto f  the p o te n t ial for bi ase s int h e relevant evid e nc e , reg ardles s of w hethero r n ot  it was  po s s ible forthe respe c tiv estud ies to a vo id s uc h b ia ses. There arescenario s, thoug h ,  in wh ich we m i ght ha ve  reasons tothink  t h at a pr o p ert y of as tud y t hat  cau ses  bia s  in other scenarios does  not  caus e  bi as
 Moreover,_this low_inter-tool reliability has philosophical_consequences, which_I_explore in_§5._Such low inter-tool_reliability might be_less troubling if the_various QATs had_distinct_domains of application. The many biases present in medical research are pertinent to varying_degrees_depending on_the_details_of the particular circumstances at_hand, and so one might_think that_it is a mistake to expect that one_QAT_ought to apply_to all circumstances. For some causal hypotheses, for instance,_it is difficult or impossible to_conceal the treatment_from_the_experimental subjects and/or the_investigators (that is, 'blinding' is sometimes_impossible)-hypotheses regarding chiropractic spinal manipulation are_a case in point. Thus, no study_relevant to such a hypothesis will_score well on a QAT_that gives_a large weight to allocation_concealment. Such a_QAT would_be less sensitive_to the presence or absence of_sources of bias_other than lack of allocation concealment,_relative_to QATs that_give_little_or no_weight to allocation_concealment._In such_a_case one might argue that since_the_absence of allocation concealment is fixed among_the relevant studies, an_appropriate_QAT to use in_this case should not give_any weight to allocation concealment, and_would only_ask about_the presence of those properties of a study that might vary_among the relevant studies. On the_other hand, one might_argue that_since_we have principled_reasons_for thinking_that the absence of allocation concealment can_bias the_results of a study, even among_those studies that cannot_possibly_conceal subject allocation, an appropriate QAT_to use in this case should_evaluate the presence of allocation_concealment_(in_which case all of the_relevant studies would simply receive a_zero score on_allocation concealment), just as a QAT ought_to_evaluate the presence of allocation concealment_in_a scenario in which the studies_in_fact_can conceal subject allocation. The_former consideration is an appeal to_determining the relative quality between studies, and the latter_consideration is an_appeal to determining the absolute_quality_of_studies. The latter consideration should be more compelling in most_cases, since,_as discussed above,_the typical use of QATs is to help estimate the_true efficacy of a medical intervention, and_such estimates ought to take into account the full extent of_the potential for biases in the relevant evidence,_regardless of whether or not it was_possible for the respective_studies_to avoid such biases. There are scenarios,_though,_in_which_we might have_reasons to think_that a property_of a_study that causes_bias in_other scenarios does_not_cause bias